Dissertations / Theses on the topic 'World Wide Web. Search engines'

Thesis (MSc)--Stellenbosch University, 2003.<br>ENGLISH ABSTRACT: We present DEADLINER, a special-purpose search engine that indexes conference and workshop announcements, and which extracts a range of academic information from the Web. SVMs provide an efficient and highly accurate mechanism for obtaining relevant web documents. DEADLINER currently extracts speakers, locations (e.g. countries), dates, paper submission (and other) deadlines, topics, program committees, abstracts, and affiliations. Complex and detailed searches are possible on these fields. The niche search engine was constructed by employing a methodology for rapid implementation of specialised search engines. Bayesian integration of simple extractors provides this methodology, that avoids complex hand-tuned text extraction methods. The simple extractors exploit loose formatting and keyword conventions. The Bayesian framework further produces a search engine where each user can control each fields false alarm rate in an intuitive and rigorous fashion, thus providing easy-to-use metadata.<br>AFRIKAANSE OPSOMMING: Ons stel DEADLINER bekend: 'n soekmasjien wat konferensie en werkvergaderingsaankondigings katalogiseer en wat uiteindelik 'n wye reeks akademiese byeenkomsmateriaal sal monitor en onttrek uit die Web. DEAD LINER herken en onttrek tans sprekers, plekke (bv. landname), datums, o.a. sperdatums vir die inlewering van akademiese verrigtings, onderwerpe, programkomiteë, oorsigte of opsommings, en affiliasies. 'n Grondige soek is moontlik oor en deur hierdie velde. Die nissoekmasjien is gebou deur gebruik te maak van 'n metodologie vir die vinnige oprigting van spesialiteitsoekmasjiene. Die metodologie vermy komplekse instelling m.b.v. hande-arbeid van die teksuittreksels deur gebruik te maak van Bayesiese integrering van eenvoudige ontsluiters. Die ontsluiters buit dan styl- en gewoonte-sleutelwoorde uit. Die Bayesiese raamwerk skep hierdeur 'n soekmasjien wat gebruikers toelaat om elke veld se kans om verkeerd te kies op 'n intuïtiewe en deeglike manier te beheer.

The main contribution of this dissertation is a system for locating and indexing audio files on the World Wide Web. The idea behind this system is that the use of both web page and audio file analysis techniques can produce more relevant information for locating audio files on the web than is used in full-text search engines.<br>The most important part of this system is a web crawler that finds materials by following hyperlinks between web pages. The crawler is distributed and operates using multiple computers across a network, storing results to a database. There are two main components: a set of retrievers that retrieve pages and audio files from the web, and a central crawl manager that coordinates the retrievers and handles data storage tasks.<br>The crawler is designed to locate three types of audio files: AIFF, WAVE, and MPEG-1 (MP3), but other types can be easily added to the system. Once audio files are located, analyses are performed of both the audio files and the associated web pages that link to these files. Information extracted by the crawler can be used to build search indexes for resolving user queries. A set of results demonstrating aspects of the performance of the crawler are presented, as well as some statistics and points of interest regarding the nature of audio files on the web.

Thesis (M.S.)--Kent State University, 2007.<br>Title from PDF t.p. (viewed July 2, 2007). Advisor: David B. Robins. Keywords: information retrieval, search engine, social bookmarking, tagging, folksonomy, Internet, World Wide Web. Includes survey instrument. Includes bibliographical references (p. 137-141).

Search engines are essential components of the World Wide Web; both commercially and in terms of everyday usage, their importance is hard to overstate. This thesis examines the question of why there is bias in search engine results – bias that invites users to click on links to large websites, commercial websites, websites based in certain countries, and websites written in certain languages. In this thesis, the historical development of the search engine industry is traced. Search engines first emerged as prototypical technological startups emanating from Silicon Valley, followed by the acquisition of search engine companies by major US media corporations and their development into portals. The subsequent development of pay-per-click advertising is central to the current industry structure, an oligarchy of virtually integrated companies managing networks of syndicated advertising and traffic distribution. The study also shows a global landscape in which search production is concentrated in and caters for large global advertising markets, leaving the rest of the world with patchy and uneven search results coverage. The analysis of interviews with senior search engine engineers indicates that issues of quality are addressed in terms of customer service and relevance in their discourse, while the analysis of documents, interviews with search marketers, and participant observation within a search engine marketing firm showed that producers and marketers had complex relationships that combine aspects of collaboration, competition, and indifference. The results of the study offer a basis for the synthesis of insights of the political economy of media and communication and the social studies of technology tradition, emphasising the importance of culture in constructing and maintaining both local structures and wider systems. In the case of search engines, the evidence indicates that the culture of the technological entrepreneur is very effective in creating a new megabusiness, but less successful in encouraging a debate on issues of the public good or public responsibility as they relate to the search engine industry.

This research is an integral part of the effort aimed at overcoming the limitations of the classic search engines. This thesis is concerned with the investigation of the impact of different modes of mediation on the web search process. Conceptually, it is divided into three main parts. The first part details the investigation of methods and mechanisms in user profile generation and in filtering search results. The second part deals with the presentation of an approach and its application in the development of a mediation framework between the user and the classic Web Search engines. This involved the integration of the explicit, implicit and hybrid modes of mediation within a content-based method, and was facilitated by the adoption of the Vector Space Model. The third part presents an extensive comparative evaluation of the impact of the different types of mediation systems on web search, in terms of precision, recall and F-measure. The thesis concludes by identifying the contribution of the research programme and the satisfaction of the stated objectives.

Search engines are currently the most popular method of information retrieval on the World Wide Web. However, researchers have not thoroughly examined search engines as they are used and judged by novice end-users. Calumet College of St. Joseph (CCSJ) required an investigation of search engine results to reveal how Web search engines supported the information seeking of CCSJ students. This study determined the effectiveness of information gathering through six popular search engines: Excite, Google, Lycos, MSN, Northern Light, and Yahoo!. It included an investigation of the relevance of search engine results as established by end-user relevance judgments made by novice information seekers, CCSJ students. Students in seven CCSJ English classes participated in this study. A questionnaire gathered demographic data and information about students' computer use, information retrieval experience, and experience with the World Wide Web. Students searched six search engines with search topics and queries of their choice and ranked the first \0 results according to their own relevance judgments (1 was most relevant and 10 was least relevant) . The Pearson Product Moment Correlation Coefficient determined what correlation existed between the relevance rankings of the search engines and the rankings of the students. Results showed a low correlation, though a test of significance determined that this correlation is not statistically significant. Therefore, currently popular search engines are not effective in retrieving results for information-seeking CCSJ students though they may be successful some of the time. No search engine outperformed the others in this experiment, though it is also evident that no search engine consistently performed badly enough to indicate that it was the poorest performer. Furthermore, the frequency with which students used the Web, online databases/indexes, and search engines was highly correlated with search success. Two issues surfaced during the course of this study: some students' lack of computer skills, and some students' inability to construct appropriate search statements. CCSJ should take action in the areas of computer literacy and information literacy (specifically information retrieval on the World Wide Web) in order to prepare these students for the increased importance of this popular measure of information retrieval in their lives.

Thesis submitted in fulfilment of the requirements for the degree Magister Technologiae in Information Technology in the Faculty of Informatics and Design 2006<br>The primary objective of this research project was to determine whether search engine optimisation elements as specified in the Chambers model, affect real estate website visibility. In South Africa, real estate companies predominantly function as SMMEs and are therefore as vulnerable to failure as any other SMME in the country. In order for SMMEs to reduce the possibility of failure, they need to re-evaluate their use of the Internet, as it could assist in their survival. The traditional company structure is no longer sufficient to ensure market reward. The reality is that users are rapidly adapting to the technology available. The Internet is fast becoming a communication, commerce and marketing medium that is changing business globally. Real estate SMMEs are unable to adapt to e-commerce in its purest form, however, they can make effective use of e-marketing. Static websites are used for that specific purpose. A marketing strategy is imperative to the survival of a company, whereby the firm is able to create and maintain a competitive advantage in a cluttered marketplace. Regrettably, hosting a website on the Internet is not enough. Searchers tend not to view search results beyond the second page - 30 results at the most. It becomes evident that companies should ensure that their own website ranks as high as possible on the search engine result page. This in turn should sufficiently market the company. Search engine optimisation involves designing or modifying websites in order to improve search engine result page ranking. The elements as specified in the Chambers model are extensively elaborated on in the literature analysis. The methodology consisted of two stages - a questionnaire and empirical experiments. A quantitative research approach was adopted for both of these components. The primary objective of the questionnaire was to obtain search phrases from the public when searching for real estate online. The search phrases were then used in the experiments, testing the visibility of predetermined websites, which were based on a pre- post- test control group design methodology. In this instance, the before group consisted of five different websites from five different real estate companies which have been hosted on the Internet for a duration of no less than three months. The Chambers model was used in the development of five new optimised websites, one for each company. The new websites were hosted on the Internet for 27 days, in order to give search engines the opportunity to index them. The results documented were then compared in order to draw a conclusion. A total of 121 key search phrases were obtained. The results from the old and new websites were applied to a process which produced a combination of results known as the ‘quality factor’. The quality factor indicated either a visibility improvement or visibility deterioration with regard to the old and new company’s website. In addition to this, this author compared the optimised website which obtained the best visibility improvement with the website that obtained the highest deterioration in visibility. As a result, the elements specified in the Chambers model were re-evaluated whereby new elements that had not been specified in the original model were identified. Based on the new findings, this author developed a new search engine optimisation model as a secondary objective in this thesis.

Five years have passed since Helen R. Tibbo and Lokman I. Meho conducted their study exploring how well six Web search engines retrieved electronic finding aids based on phrase and word searches of terms taken directly from the finding aids. This study similarly seeks to discover how well current search engines Google, Yahoo! Search, MSN Search, AOL Search, Excite, and Ask Jeeves retrieved finding aids chosen at random from 25 North American primary source repositories. In March 2005, approximately 27% of repositories listed at the “Repositories of Primary Resources” web site had at least four full finding aids online, a substantial increase from 8% in 2000. This study affirmed phrase searches yielding better retrieval results than word searches. Encouragingly, the retrieval rates for phrase and word searches within electronic finding aids were approximately 20% higher than Tibbo and Meho’s findings despite the existence of several billion more World Wide Web pages in 2005.

Over the past 25 years, search engines have become one of the most important, if not the entry point of the World Wide Web. This development has been primarily due to the continuously increasing amount of available documents, which are highly unstructured. Moreover, the general trend is towards classifying search results into categories and presenting them in terms of semantic information that answer users' queries without having to leave the search engine. With the growing amount of documents and technological enhancements, the needs of users as well as search engines are continuously evolving. Users want to be presented with increasingly sophisticated results and interfaces while companies have to place advertisements and make revenue to be able to offer their services for free. To address the above needs, it is more and more important to provide highly usable and optimized search engine results pages (SERPs). Yet, existing approaches to usability evaluation are often costly or time-consuming and mostly rely on explicit feedback. They are either not efficient or not effective while SERP interfaces are commonly optimized primarily from a company's point of view. Moreover, existing approaches to predicting search result relevance, which are mostly based on clicks, are not tailored to the evolving kinds of SERPs. For instance, they fail if queries are answered directly on a SERP and no clicks need to happen. Applying Human-Centered Design principles, we propose a solution to the above in terms of a holistic approach that intends to satisfy both, searchers and developers. It provides novel means to counteract exclusively company-centric design and to make use of implicit user feedback for efficient and effective evaluation and optimization of usability and, in particular, relevance. We define personas and scenarios from which we infer unsolved problems and a set of well-defined requirements. Based on these requirements, we design and develop the Search Interaction Optimization toolkit. Using a bottom-up approach, we moreover define an eponymous, higher-level methodology. The Search Interaction Optimization toolkit comprises a total of six components. We start with INUIT [1], which is a novel minimal usability instrument specifically aiming at meaningful correlations with implicit user feedback in terms of client-side interactions. Hence, it serves as a basis for deriving usability scores directly from user behavior. INUIT has been designed based on reviews of established usability standards and guidelines as well as interviews with nine dedicated usability experts. Its feasibility and effectiveness have been investigated in a user study. Also, a confirmatory factor analysis shows that the instrument can reasonably well describe real-world perceptions of usability. Subsequently, we introduce WaPPU [2], which is a context-aware A/B testing tool based on INUIT. WaPPU implements the novel concept of Usability-based Split Testing and enables automatic usability evaluation of arbitrary SERP interfaces based on a quantitative score that is derived directly from user interactions. For this, usability models are automatically trained and applied based on machine learning techniques. In particular, the tool is not restricted to evaluating SERPs, but can be used with any web interface. Building on the above, we introduce S.O.S., the SERP Optimization Suite [3], which comprises WaPPU as well as a catalog of best practices [4]. Once it has been detected that an investigated SERP's usability is suboptimal based on scores delivered by WaPPU, corresponding optimizations are automatically proposed based on the catalog of best practices. This catalog has been compiled in a three-step process involving reviews of existing SERP interfaces and contributions by 20 dedicated usability experts. While the above focus on the general usability of SERPs, presenting the most relevant results is specifically important for search engines. Hence, our toolkit contains TellMyRelevance! (TMR) [5] — the first end-to-end pipeline for predicting search result relevance based on users’ interactions beyond clicks. TMR is a fully automatic approach that collects necessary information on the client, processes it on the server side and trains corresponding relevance models based on machine learning techniques. Predictions made by these models can then be fed back into the ranking process of the search engine, which improves result quality and hence also usability. StreamMyRelevance! (SMR) [6] takes the concept of TMR one step further by providing a streaming-based version. That is, SMR collects and processes interaction data and trains relevance models in near real-time. Based on a user study and large-scale log analysis involving real-world search engines, we have evaluated the components of the Search Interaction Optimization toolkit as a whole—also to demonstrate the interplay of the different components. S.O.S., WaPPU and INUIT have been engaged in the evaluation and optimization of a real-world SERP interface. Results show that our tools are able to correctly identify even subtle differences in usability. Moreover, optimizations proposed by S.O.S. significantly improved the usability of the investigated and redesigned SERP. TMR and SMR have been evaluated in a GB-scale interaction log analysis as well using data from real-world search engines. Our findings indicate that they are able to yield predictions that are better than those of competing state-of-the-art systems considering clicks only. Also, a comparison of SMR to existing solutions shows its superiority in terms of efficiency, robustness and scalability. The thesis concludes with a discussion of the potential and limitations of the above contributions and provides an overview of potential future work<br>Im Laufe der vergangenen 25 Jahre haben sich Suchmaschinen zu einem der wichtigsten, wenn nicht gar dem wichtigsten Zugangspunkt zum World Wide Web (WWW) entwickelt. Diese Entwicklung resultiert vor allem aus der kontinuierlich steigenden Zahl an Dokumenten, welche im WWW verfügbar, jedoch sehr unstrukturiert organisiert sind. Überdies werden Suchergebnisse immer häufiger in Kategorien klassifiziert und in Form semantischer Informationen bereitgestellt, die direkt in der Suchmaschine konsumiert werden können. Dies spiegelt einen allgemeinen Trend wider. Durch die wachsende Zahl an Dokumenten und technologischen Neuerungen wandeln sich die Bedürfnisse von sowohl Nutzern als auch Suchmaschinen ständig. Nutzer wollen mit immer besseren Suchergebnissen und Interfaces versorgt werden, während Suchmaschinen-Unternehmen Werbung platzieren und Gewinn machen müssen, um ihre Dienste kostenlos anbieten zu können. Damit geht die Notwendigkeit einher, in hohem Maße benutzbare und optimierte Suchergebnisseiten – sogenannte SERPs (search engine results pages) – für Nutzer bereitzustellen. Gängige Methoden zur Evaluierung und Optimierung von Usability sind jedoch größtenteils kostspielig oder zeitaufwändig und basieren meist auf explizitem Feedback. Sie sind somit entweder nicht effizient oder nicht effektiv, weshalb Optimierungen an Suchmaschinen-Schnittstellen häufig primär aus dem Unternehmensblickwinkel heraus durchgeführt werden. Des Weiteren sind bestehende Methoden zur Vorhersage der Relevanz von Suchergebnissen, welche größtenteils auf der Auswertung von Klicks basieren, nicht auf neuartige SERPs zugeschnitten. Zum Beispiel versagen diese, wenn Suchanfragen direkt auf der Suchergebnisseite beantwortet werden und der Nutzer nicht klicken muss. Basierend auf den Prinzipien des nutzerzentrierten Designs entwickeln wir eine Lösung in Form eines ganzheitlichen Ansatzes für die oben beschriebenen Probleme. Dieser Ansatz orientiert sich sowohl an Nutzern als auch an Entwicklern. Unsere Lösung stellt automatische Methoden bereit, um unternehmenszentriertem Design entgegenzuwirken und implizites Nutzerfeedback für die effizienteund effektive Evaluierung und Optimierung von Usability und insbesondere Ergebnisrelevanz nutzen zu können. Wir definieren Personas und Szenarien, aus denen wir ungelöste Probleme und konkrete Anforderungen ableiten. Basierend auf diesen Anforderungen entwickeln wir einen entsprechenden Werkzeugkasten, das Search Interaction Optimization Toolkit. Mittels eines Bottom-up-Ansatzes definieren wir zudem eine gleichnamige Methodik auf einem höheren Abstraktionsniveau. Das Search Interaction Optimization Toolkit besteht aus insgesamt sechs Komponenten. Zunächst präsentieren wir INUIT [1], ein neuartiges, minimales Instrument zur Bestimmung von Usability, welches speziell auf sinnvolle Korrelationen mit implizitem Nutzerfeedback in Form Client-seitiger Interaktionen abzielt. Aus diesem Grund dient es als Basis für die direkte Herleitung quantitativer Usability-Bewertungen aus dem Verhalten von Nutzern. Das Instrument wurde basierend auf Untersuchungen etablierter Usability-Standards und -Richtlinien sowie Experteninterviews entworfen. Die Machbarkeit und Effektivität der Benutzung von INUIT wurden in einer Nutzerstudie untersucht und darüber hinaus durch eine konfirmatorische Faktorenanalyse bestätigt. Im Anschluss beschreiben wir WaPPU [2], welches ein kontextsensitives, auf INUIT basierendes Tool zur Durchführung von A/B-Tests ist. Es implementiert das neuartige Konzept des Usability-based Split Testing und ermöglicht die automatische Evaluierung der Usability beliebiger SERPs basierend auf den bereits zuvor angesprochenen quantitativen Bewertungen, welche direkt aus Nutzerinteraktionen abgeleitet werden. Hierzu werden Techniken des maschinellen Lernens angewendet, um automatisch entsprechende Usability-Modelle generieren und anwenden zu können. WaPPU ist insbesondere nicht auf die Evaluierung von Suchergebnisseiten beschränkt, sondern kann auf jede beliebige Web-Schnittstelle in Form einer Webseite angewendet werden. Darauf aufbauend beschreiben wir S.O.S., die SERP Optimization Suite [3], welche das Tool WaPPU sowie einen neuartigen Katalog von „Best Practices“ [4] umfasst. Sobald eine durch WaPPU gemessene, suboptimale Usability-Bewertung festgestellt wird, werden – basierend auf dem Katalog von „Best Practices“ – automatisch entsprechende Gegenmaßnahmen und Optimierungen für die untersuchte Suchergebnisseite vorgeschlagen. Der Katalog wurde in einem dreistufigen Prozess erarbeitet, welcher die Untersuchung bestehender Suchergebnisseiten sowie eine Anpassung und Verifikation durch 20 Usability-Experten beinhaltete. Die bisher angesprochenen Tools fokussieren auf die generelle Usability von SERPs, jedoch ist insbesondere die Darstellung der für den Nutzer relevantesten Ergebnisse eminent wichtig für eine Suchmaschine. Da Relevanz eine Untermenge von Usability ist, beinhaltet unser Werkzeugkasten daher das Tool TellMyRelevance! (TMR) [5], die erste End-to-End-Lösung zur Vorhersage von Suchergebnisrelevanz basierend auf Client-seitigen Nutzerinteraktionen. TMR ist einvollautomatischer Ansatz, welcher die benötigten Daten auf dem Client abgreift, sie auf dem Server verarbeitet und entsprechende Relevanzmodelle bereitstellt. Die von diesen Modellen getroffenen Vorhersagen können wiederum in den Ranking-Prozess der Suchmaschine eingepflegt werden, was schlussendlich zu einer Verbesserung der Usability führt. StreamMyRelevance! (SMR) [6] erweitert das Konzept von TMR, indem es einen Streaming-basierten Ansatz bereitstellt. Hierbei geschieht die Sammlung und Verarbeitung der Daten sowie die Bereitstellung der Relevanzmodelle in Nahe-Echtzeit. Basierend auf umfangreichen Nutzerstudien mit echten Suchmaschinen haben wir den entwickelten Werkzeugkasten als Ganzes evaluiert, auch, um das Zusammenspiel der einzelnen Komponenten zu demonstrieren. S.O.S., WaPPU und INUIT wurden zur Evaluierung und Optimierung einer realen Suchergebnisseite herangezogen. Die Ergebnisse zeigen, dass unsere Tools in der Lage sind, auch kleine Abweichungen in der Usability korrekt zu identifizieren. Zudem haben die von S.O.S.vorgeschlagenen Optimierungen zu einer signifikanten Verbesserung der Usability der untersuchten und überarbeiteten Suchergebnisseite geführt. TMR und SMR wurden mit Datenmengen im zweistelligen Gigabyte-Bereich evaluiert, welche von zwei realen Hotelbuchungsportalen stammen. Beide zeigen das Potential, bessere Vorhersagen zu liefern als konkurrierende Systeme, welche lediglich Klicks auf Ergebnissen betrachten. SMR zeigt gegenüber allen anderen untersuchten Systemen zudem deutliche Vorteile bei Effizienz, Robustheit und Skalierbarkeit. Die Dissertation schließt mit einer Diskussion des Potentials und der Limitierungen der erarbeiteten Forschungsbeiträge und gibt einen Überblick über potentielle weiterführende und zukünftige Forschungsarbeiten

Careful examination of the composition and concentration of malicious traffic in transit on the channels of the Internet provides network administrators with a means of understanding and predicting damaging attacks directed towards their networks. This allows for action to be taken to mitigate the effect that these attacks have on the performance of their networks and the Internet as a whole by readying network defences and providing early warning to Internet users. One approach to malicious traffic monitoring that has garnered some success in recent times, as exhibited by the study of fast spreading Internet worms, involves analysing data obtained from network telescopes. While some research has considered using measures derived from network telescope datasets to study large scale network incidents such as Code-Red, SQLSlammer and Conficker, there is very little documented discussion on the merits and weaknesses of approaches to analyzing network telescope data. This thesis is an introductory study in network telescope analysis and aims to consider the variables associated with the data received by network telescopes and how these variables may be analysed. The core research of this thesis considers both novel and previously explored analysis techniques from the fields of security metrics, baseline analysis, statistical analysis and technical analysis as applied to analysing network telescope datasets. These techniques were evaluated as approaches to recognize unusual behaviour by observing the ability of these techniques to identify notable incidents in network telescope datasets

Made available in DSpace on 2014-06-11T19:29:41Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-08-03Bitstream added on 2014-06-13T20:59:57Z : No. of bitstreams: 1 garcia_lmls_me_sjrp.pdf: 6057674 bytes, checksum: a26fce0d239fd5ca19b1f04d3236faa6 (MD5)<br>Quando fala-se de evolução da Web, poderia realmente ser mais apropriado falar de design inteligente. Com a Web se tornando a principal opção para quem produz e dissemina conteúdo digital, cada vez mais, as pessoas tomam a atenção para esse valioso repositório de conhecimento. Neste ambiente, os mecanismos de busca configuram-se em aplicativos populares, tornando-se intermediários entre os usuários e a miríade de informações, serviços e recursos disponíveis na grande rede. Neste sentido, o Webdesigner pode atuar de forma decisiva, proporcionando uma melhor resposta na classificação dos mecanismos de busca. A correta representação do conhecimento é a chave para a recuperação e para a disseminação efetiva de dados, de informação e de conhecimentos. Este trabalho apresenta um estudo que pode trazer um progresso relevante aos usuários desta grande rede, buscando apresentar uma ferramenta de domínio público que apoie a aplicação de técnicas de descrição semântica de informação na Web. No decorrer da pesquisa investigamos técnicas e metodologias capazes de otimizar a indexação dos Websites pelos mecanismos de busca, enfatizando a descrição do conteúdo nele presente, melhorando sua classificação e consequentemente colaborando com a qualidade na recuperação de informações realizadas por meio de mecanismos de buscas. Tais técnicas foram testadas em alguns Websites, obtendo resultado satisfatório, a partir de então a ferramenta foi implementada e submetida a usuários para sua validação, o resultado desta validação é apresentado demonstrando a viabilidade da ferramenta e enumeração de novas funcionalidades para trabalhos futuros<br>When we speak of evolution of the Web, it might actually be more appropriate to speak of intelligent design. With the Web becoming the primary choice for those who produce and disseminate digital content , more people take attention to this valuable repository of knowledge. In this environment , search engines are configured in popular, becoming an intermediary between users and the myriad of information, service and resources available on the World Wide Web. In this sense, the Web designer can act decisively, providing a better response in the ranking of search engines. The correct representation of knowledge is the key to recovery and effective dissemination of data, information and knowledge. This paper presents a study that significant progress can bring a large network of users, seeking to present a public domain tool that supports the application of techniques for semantic description of Web information in the course of the research investigated techniques and methodologies that can optimize Website indexing by search engines, emphasizing the description of the content in it, improving your ranking and thus contributing to quality in information retrieval conducted through search engines. These techniques were tested on some websites, obtaining satisfactory results, since then the tool was implemented and submitted to users validation, the result of the validation is present demonstrating the feasibility of the tool and list of new features for future work

Resumo: Quando fala-se de evolução da Web, poderia realmente ser mais apropriado falar de design inteligente. Com a Web se tornando a principal opção para quem produz e dissemina conteúdo digital, cada vez mais, as pessoas tomam a atenção para esse valioso repositório de conhecimento. Neste ambiente, os mecanismos de busca configuram-se em aplicativos populares, tornando-se intermediários entre os usuários e a miríade de informações, serviços e recursos disponíveis na grande rede. Neste sentido, o Webdesigner pode atuar de forma decisiva, proporcionando uma melhor resposta na classificação dos mecanismos de busca. A correta representação do conhecimento é a chave para a recuperação e para a disseminação efetiva de dados, de informação e de conhecimentos. Este trabalho apresenta um estudo que pode trazer um progresso relevante aos usuários desta grande rede, buscando apresentar uma ferramenta de domínio público que apoie a aplicação de técnicas de descrição semântica de informação na Web. No decorrer da pesquisa investigamos técnicas e metodologias capazes de otimizar a indexação dos Websites pelos mecanismos de busca, enfatizando a descrição do conteúdo nele presente, melhorando sua classificação e consequentemente colaborando com a qualidade na recuperação de informações realizadas por meio de mecanismos de buscas. Tais técnicas foram testadas em alguns Websites, obtendo resultado satisfatório, a partir de então a ferramenta foi implementada e submetida a usuários para sua validação, o resultado desta validação é apresentado demonstrando a viabilidade da ferramenta e enumeração de novas funcionalidades para trabalhos futuros<br>Abstract: When we speak of evolution of the Web, it might actually be more appropriate to speak of intelligent design. With the Web becoming the primary choice for those who produce and disseminate digital content , more people take attention to this valuable repository of knowledge. In this environment , search engines are configured in popular, becoming an intermediary between users and the myriad of information, service and resources available on the World Wide Web. In this sense, the Web designer can act decisively, providing a better response in the ranking of search engines. The correct representation of knowledge is the key to recovery and effective dissemination of data, information and knowledge. This paper presents a study that significant progress can bring a large network of users, seeking to present a public domain tool that supports the application of techniques for semantic description of Web information in the course of the research investigated techniques and methodologies that can optimize Website indexing by search engines, emphasizing the description of the content in it, improving your ranking and thus contributing to quality in information retrieval conducted through search engines. These techniques were tested on some websites, obtaining satisfactory results, since then the tool was implemented and submitted to users validation, the result of the validation is present demonstrating the feasibility of the tool and list of new features for future work<br>Orientador: João Fernando Marar<br>Coorientador: Ivan Rizzo Guilherme<br>Banca: Edson Costa de Barros Carvalho Filho<br>Banca: Antonio Carlos Sementille<br>Mestre

This thesis was built on a practical work for LM Ericsson Data AB and deals with how toexamine an information need for a limited department within the corporation using aqualitative interview method.The thesis deals with how to search for requested information on the Internet and the WorldWide Web (WWW). It contains a model and a method for evaluation of search engines onthe World Wide Web, and 16 search engines which primarily indexes the World Wide Webare being evaluated.

<p>Millions of people are using search engines every day when they are trying to find information on the Internet. The purpose of this report is to find out how people formulate search queries. The result in this report is based on an empirical study which is based on a search log from the Swedish search engine Seek.se.</p><p>One of the results in this thesis is that nearly all search queries are based on keywords.</p><br><p>Miljoner människor använder sökmotorer varje dag när de försöker hitta information på Internet. Syftet med den här uppsatsen är att ta reda på hur individer formulerar sökfraser. Resultatet i rapporten är baserad på en empirisk studie som är baserad på sökloggen för den svenska sökmotorn Seek.se.</p><p>Uppsatsen kommer bl.a. fram till att nästan alla sökningar som görs på Internet är nyckelordsbaserade.</p>

Entertainics is a web-based software application used to gather information about DVD players from several web-sites on the internet. The purpose of this software is to help users search for DVD players in a faster and easier way, by avoiding the navigation on every web-site that contains this product.

Every scientific research begins with a literature review that includes an extensive bibliographic search. Such searches are known to be difficult and time-consuming because of the vast amount of topical material existing in today's ever-changing technology base. Keeping up-to-date with related literature and being aware of the most recent publications require extensive time and effort. The need for a WWW-based software tool for collecting and providing access to this scientific body of knowledge is undeniable. The study explained herein deals with this problem by developing an efficient, advanced, easy-to-use tool, WebBiblio, that provides a globally accessible WWW environment enabling the collection and dissemination of searchable bibliographies comprised of abstracts and keywords. This thesis describes the design, structure and features of WebBiblio, and explains the ideas and approaches used in its development. The developed system is not a prototype, but a production system that exploits the capabilities of the WWW. Currently, it is used to publish three VV&T bibliographies at the WWW site: http://manta.cs.vt.edu/biblio. With its rich set of features and ergonomically engineered interface, WebBiblio brings a comprehensive solution to solving the problem of globally collecting and providing access to a diverse set of bibliographies.<br>Master of Science

The vast amount of data available over the World Wide Web has created the necessity for new initiatives that translate this data into useful information for users. Due to human's acute visual perception, applications that utilize information visualization CIV) methodologies may ease user frustration when facing an abundance of search results from an Internet query. The recent introduction of ditto.com, an Internet search engine that provides users with a graphical depiction of search results documents, is a recent initiative that employs IV methodologies. This research is based upon the usability of traditional information retrieval systems and Internet search applications, and the impact IV methodologies have had on these systems. A usability evaluation was recently implemented to determine if IV methodologies can facilitate users' search needs when searching for information over the Internet. Fifteen randomly selected participants that match the diversity of Web users were asked to compare two Internet search results interfaces: Yahoo! a search engine that provides users with text-based search results and the graphical displays found within ditto.com. Descriptive data was collected through usability questionnaires and observing users search for information. Measurable data was collected by testing the performance of each search engine as the users search for ready-reference questions. Time to complete search tasks, the accuracy of the tasks, and number of error rates was collected from this session. Users were asked to provide their preference for one of the search engines. The data was analyzed for mean averages, occurrence of specific incidents that help or hindered users, and distribution of results with user experience. The results of this study are presented in a narrative report of users' preferences and concerns.

Orientador: Ricardo da Silva Torres<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação<br>Made available in DSpace on 2018-08-13T11:00:01Z (GMT). No. of bitstreams: 1 Penatti_OtavioAugustoBizetto_M.pdf: 2250748 bytes, checksum: 57d5b2f9120a8eae69ee9881d363e9ce (MD5) Previous issue date: 2009<br>Resumo: A crescente quantidade de imagens geradas e disponibilizadas atualmente tem eito aumentar a necessidade de criação de sistemas de busca para este tipo de informação. Um método promissor para a realização da busca de imagens e a busca por conteúdo. Este tipo de abordagem considera o conteúdo visual das imagens, como cor, textura e forma de objetos, para indexação e recuperação. A busca de imagens por conteúdo tem como componente principal o descritor de imagens. O descritor de imagens é responsável por extrair propriedades visuais das imagens e armazená-las em vetores de características. Dados dois vetores de características, o descritor compara-os e retorna um valor de distancia. Este valor quantifica a diferença entre as imagens representadas pelos vetores. Em um sistema de busca de imagens por conteúdo, a distancia calculada pelo descritor de imagens é usada para ordenar as imagens da base em relação a uma determinada imagem de consulta. Esta dissertação realiza um estudo comparativo de descritores de imagens considerando a Web como cenário de uso. Este cenário apresenta uma quantidade muito grande de imagens e de conteúdo bastante heterogêneo. O estudo comparativo realizado nesta dissertação é feito em duas abordagens. A primeira delas considera a complexidade assinto tica dos algoritmos de extração de vetores de características e das funções de distancia dos descritores, os tamanhos dos vetores de características gerados pelos descritores e o ambiente no qual cada descritor foi validado originalmente. A segunda abordagem compara os descritores em experimentos práticos em quatro bases de imagens diferentes. Os descritores são avaliados segundo tempo de extração, tempo para cálculos de distancia, requisitos de armazenamento e eficácia. São comparados descritores de cor, textura e forma. Os experimentos são realizados com cada tipo de descritor independentemente e, baseado nestes resultados, um conjunto de descritores é avaliado em uma base com mais de 230 mil imagens heterogêneas, que reflete o conteúdo encontrado na Web. A avaliação de eficácia dos descritores na base de imagens heterogêneas é realizada por meio de experimentos com usuários reais. Esta dissertação também apresenta uma ferramenta para a realização automatizada de testes comparativos entre descritores de imagens.<br>Abstract: The growth in size of image collections and the worldwide availability of these collections has increased the demand for image retrieval systems. A promising approach to address this demand is to retrieve images based on image content (Content-Based Image Retrieval). This approach considers the image visual properties, like color, texture and shape of objects, for indexing and retrieval. The main component of a content-based image retrieval system is the image descriptor. The image descriptor is responsible for encoding image properties into feature vectors. Given two feature vectors, the descriptor compares them and computes a distance value. This value quantifies the difference between the images represented by their vectors. In a content-based image retrieval system, these distance values are used to rank database images with respect to their distance to a given query image. This dissertation presents a comparative study of image descriptors considering the Web as the environment of use. This environment presents a huge amount of images with heterogeneous content. The comparative study was conducted by taking into account two approaches. The first approach considers the asymptotic complexity of feature vectors extraction algorithms and distance functions, the size of the feature vectors generated by the descriptors and the environment where each descriptor was validated. The second approach compares the descriptors in practical experiments using four different image databases. The evaluation considers the time required for features extraction, the time for computing distance values, the storage requirements and the effectiveness of each descriptor. Color, texture, and shape descriptors were compared. The experiments were performed with each kind of descriptor independently and, based on these results, a set of descriptors was evaluated in an image database containing more than 230 thousand heterogeneous images, reflecting the content existent in the Web. The evaluation of descriptors effectiveness in the heterogeneous database was made by experiments using real users. This dissertation also presents a tool for executing experiments aiming to evaluate image descriptors.<br>Mestrado<br>Sistemas de Informação<br>Mestre em Ciência da Computação

Contextual information retrieval (CIR) is a critical technique for today’s search engines in terms of facilitating queries and returning relevant information. Despite its importance, little progress has been made in its application, due to the difficulty of capturing and representing contextual information about users. This thesis details the development and evaluation of the contextual SERL search, designed to tackle some of the challenges associated with CIR from the World Wide Web. The contextual SERL search utilises a rich contextual model that exploits implicit and explicit data to modify queries to more accurately reflect the user’s interests as well as to continually build the user’s contextual profile and a shared contextual knowledge base. These profiles are used to filter results from a standard search engine to improve the relevance of the pages displayed to the user. The contextual SERL search has been tested in an observational study that has captured both qualitative and quantitative data about the ability of the framework to improve the user’s web search experience. A total of 30 subjects, with different levels of search experience, participated in the observational study experiment. The results demonstrate that when the contextual profile and the shared contextual knowledge base are used, the contextual SERL search improves search effectiveness, efficiency and subjective satisfaction. The effectiveness improves as subjects have actually entered fewer queries to reach the target information in comparison to the contemporary search engine. In the case of a particularly complex search task, the efficiency improves as subjects have browsed fewer hits, visited fewer URLs, made fewer clicks and have taken less time to reach the target information when compared to the contemporary search engine. Finally, subjects have expressed a higher degree of satisfaction on the quality of contextual support when using the shared contextual knowledge base in comparison to using their contextual profile. These results suggest that integration of a user’s contextual factors and information seeking behaviours are very important for successful development of the CIR framework. It is believed that this framework and other similar projects will help provide the basis for the next generation of contextual information retrieval from the Web.

Using the proper search engine is crucial for efficient and effective web search. The objective of this thesis is to develop methodologies to evaluate search engines in a systematic and reliable manner. A new model for evaluation and comparison of search engines is proposed. This hierarchical model classifies the most common features found in search engines and search results into groups and subgroups. To illustrate the usefulness of the proposed model, several Chinese search engines are evaluated and compared as a case study. It is also very important to evaluate the performance of a search engine over time. Three performance measurement metrics are formulated for this purpose. Performance results for English and Chinese search engines are represented by histograms for visual inspection. The histograms are classified into groups to facilitate the interpretation of the performance metrics and examination of the associated behaviours of the search engines. An automated classification method is developed that eliminates the subjectivity and ambiguity found in visual classification of the histograms.

New Media & Society, 8(6), 2006 (forthcoming).<br>To be published in New Media & Society, 8(6), 2006 (forthcoming). Abstract: Internet search engines function in a present which changes continuously. The search engines update their indices regularly, overwriting Web pages with newer ones, adding new pages to the index, and losing older ones. Some search engines can be used to search for information at the internet for specific periods of time. However, these â date stampsâ are not determined by the first occurrence of the pages in the Web, but by the last date at which a page was updated or a new page was added, and the search engineâ s crawler updated this change in the database. This has major implications for the use of search engines in scholarly research as well as theoretical implications for the conceptions of time and temporality. We examine the interplay between the different updating frequencies by using AltaVista and Google for searches at different moments of time. Both the retrieval of the results and the structure of the retrieved information erodes over time.

by Wong, Wai Ching.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2000.<br>Includes bibliographical references (leaves 91-94).<br>Abstracts in English and Chinese.<br>Abstract --- p.ii<br>Acknowledgments --- p.v<br>Chapter 1 --- Introduction --- p.1<br>Chapter 1.1 --- Semistructured Data --- p.2<br>Chapter 1.2 --- Problem Addressed in the Thesis --- p.4<br>Chapter 1.2.1 --- Labels and Values --- p.4<br>Chapter 1.2.2 --- Discover Labels for the Same Attribute --- p.5<br>Chapter 1.2.3 --- Classifying A Web Page --- p.6<br>Chapter 1.3 --- Organization of the Thesis --- p.8<br>Chapter 2 --- Background --- p.8<br>Chapter 2.1 --- Related Work on Web Data --- p.8<br>Chapter 2.1.1 --- Object Exchange Model (OEM) --- p.9<br>Chapter 2.1.2 --- Schema Extraction --- p.11<br>Chapter 2.1.3 --- Discovering Typical Structure --- p.15<br>Chapter 2.1.4 --- Information Extraction of Web Data --- p.17<br>Chapter 2.2 --- Automatic Text Processing --- p.19<br>Chapter 2.2.1 --- Stopwords Elimination --- p.19<br>Chapter 2.2.2 --- Stemming --- p.20<br>Chapter 3 --- Web Data Definition --- p.22<br>Chapter 3.1 --- Web Page --- p.22<br>Chapter 3.2 --- Problem Description --- p.27<br>Chapter 4 --- Hierarchical Structure --- p.32<br>Chapter 4.1 --- Types of HTML Tags --- p.33<br>Chapter 4.2 --- Tag-tree --- p.36<br>Chapter 4.3 --- Hierarchical Structure Construction --- p.41<br>Chapter 4.4 --- Hierarchical Structure Statistics --- p.50<br>Chapter 5 --- Similar Labels Discovery --- p.53<br>Chapter 5.1 --- Expression of Hierarchical Structure --- p.53<br>Chapter 5.2 --- Labels Discovery Algorithm --- p.55<br>Chapter 5.2.1 --- Phase 1: Remove Non-label Nodes --- p.57<br>Chapter 5.2.2 --- Phase 2: Identify Label Nodes --- p.61<br>Chapter 5.2.3 --- Phase 3: Discover Similar Labels --- p.66<br>Chapter 5.3 --- Performance Evaluation of Labels Discovery Algorithm --- p.76<br>Chapter 5.3.1 --- Phase 1 Results --- p.75<br>Chapter 5.3.2 --- Phase 2 Results --- p.77<br>Chapter 5.3.3 --- Phase 3 Results --- p.81<br>Chapter 5.4 --- Classifying a Web Page --- p.83<br>Chapter 5.4.1 --- Similarity Measurement --- p.84<br>Chapter 5.4.2 --- Performance Evaluation --- p.86<br>Chapter 6 --- Conclusion --- p.89

This is a preprint of an article published in the Journal of Information Science Vol. 32, No. 2, 131-148 (2006). This study measures the frequency in which search engines update their indices. Therefore, 38 websites that are updated on a daily basis were analysed within a time-span of six weeks. The analysed search engines were Google, Yahoo and MSN. We find that Google performs best overall with the most pages updated on a daily basis, but only MSN is able to update all pages within a time-span of less than 20 days. Both other engines have outliers that are quite older. In terms of indexing patterns, we find different approaches at the different engines: While MSN shows clear update patterns, Google shows some outliers and the update process of the Yahoo index seems to be quite chaotic. Implications are that the quality of different search engine indices varies and not only one engine should be used when searching for current content.

Qin An.<br>Thesis (Ph.D.)--Chinese University of Hong Kong, 1998.<br>Includes bibliographical references (p. 135-142).<br>Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.<br>Mode of access: World Wide Web.<br>Abstracts in English and Chinese.

The Internet and world wide web (WWW) have in recent years, grown exponentially in size and in terms of the volume of information that is available on it. In order to effectively deal with the huge amount of information on the web, so called web search engines have been developed for the task of retrieving useful and relevant information for its users. Unfortunately, these web search engines have not kept pace with the boom growth and commercialization of the web. The main goal of this dissertation is the development of a model for a collaborative personalized meta-search agent (COPEMSA) system for the WWW. This model will enable the personalization of web search for users. Furthermore, the model aims to leverage on current search engines on the web as well as enable collaboration between users of the search system for the purposes of sharing useful resources between them. The model also employs the use of multiple intelligent agents and web content mining techniques. This enables the model to autonomously retrieve useful information for it’s user(s) and present this information in an effective manner. In order to achieve the above stated, the COPEMSA model employs the use of multiple intelligent agents. COPEMSA consists of five core components: a user agent, a query agent, a community agent, a content mining agent and a directed web spider. The user agent learns about the user in order to introduce personal preference into user queries. The query agent is a scaled down meta-search engine with the task of submitting the personalized queries it receives from the user agent to multiple search services on theWWW. The community agent enables the search system to communicate and leverage on the search experiences of a community of searchers. The content mining agent is responsible for analysis of the retrieved results from theWWWand the presentation of these results to the system user. Finally, a directed web spider is used by the content mining agent to retrieve the actual web pages it analyzes from the WWW. In this dissertation an additional model is also presented to deal with a specific problem all web spidering software must deal with namely content and link encapsulation.<br>Prof. E.M. Ehlers

The purpose of this thesis is to identify and quantify the information clues found in the document representations in the World Wide Web environment. This study uses three topics to find document representations: custom publishing, distance education, and tactile graphics. Four Web search engines are used: AltaVista, InfoSeek Ultra, Lycos, and Open Text Index. The findings of the random sample show that the search engines produce little duplication in their display of the results. Just over half of the cases reveal information clues about the document's authorship, origin, format or subject. The summary field shows the highest number of information clues. The title and Uniform Resource Locator fields do not contain many information clues. Few of the fields contain clues about the authorship of the documents. Topical relevance is questionable in many of the cases. The study recommends further research on the comparison of search engines, on the study of searches on the Web for commercial, academic and personal topics, and on information seeking behaviors relating to Web searching. Recommendations are made for Web training and Web page design to assist users in finding relevant information more quickly.

Στη διπλωματική μας παραθέτουμε ένα μεγάλο κομμάτι βιβλιογραφίας σχετικής με Τεχνικές Εξατομικευμένης Αναζήτησης στον Παγκόσμιο Ιστό. Επίσης περιγράφονται αναλυτικά οι εφαρμογές που κατασκευάστηκαν στην διπλωματική μας και οι τεχνολογίες που χρησιμοποιήθηκαν για την υλοποίησή τους. Συγκεκριμένα κατασκευάστηκε ένα σύστημα εξατομίκευσης, το οποίο καταγράφει την συμπεριφορά ενός χρήστη και στην συνέχεια του δίνει την δυνατότητα να εξατομικεύσει τα αποτελέσματα μιας μηχανής αναζήτησης(Google) με βάση την προηγούμενη συμπεριφορά του. Υλοποιήθηκαν τρεις διαφορετικοί αλγόριθμοι(ένας αλγόριθμος που βασίζεται στις ακμές του γράφου, ένας αλγόριθμος πρόσθεσης εικονικών κόμβων και ένας εκτεταμένος αλγόριθμος πρόσθεσης εικονικών κόμβων), οι οποίοι με βάση την προηγούμενη συμπεριφορά του χρήστη κατασκευάζουν ένα γράφημα συμπεριφοράς για αυτόν, το οποίο χρησιμοποιούν στη συνέχεια για να εξατομικεύσουν τα αποτελέσματα μιας ερώτησης. Οι αλγόριθμοι αυτοί καλούνται από το χρήστη μέσω του συστήματος εξατομίκευσης για μια ερώτηση και ταξινομούν τα αποτελέσματα της ερώτησης σύμφωνα με την νέα σειρά που υποδεικνύει το γράφημα συμπεριφοράς που έχει κατασκευαστεί για τον συγκεκριμένο χρήστη. Στη συνέχεια δίνονται αναλυτικά παραδείγματα λειτουργίας για κάθε αλγόριθμο, που αποδεικνύουν τους θεωρητικούς υπολογισμούς. Τέλος παρατίθενται βασικά κομμάτια του κώδικα που δημιουργήθηκε για την υλοποίηση του συστήματος εξατομίκευσης.<br>In our diplomatic we mention a big piece of bibliography relative with Techniques of Personalized Search in the World Wide Web. Also we describe analytically the applications that were manufactured in our diplomatic and the technologies that were used for their implementation. In particular, we construct a personalization system, which records the behaviour of user and then gives him the possibility of personalizing the results of a search engine (Google) with base his previous behaviour. They constructed three different algorithms(an algorithm that based on the edges of the graph, an algorithm that add virtual nodes and an extensive algorithm that add virtual nodes), which with base the previous behaviour of user construct a graph, which they use then in order to personalize the results of the query. These algorithms are called by the user via the personalization system for a query and they categorize the results of query according to the new order that indicates the graph of behaviour that has been constructed for the particular user. Then they are given analytic examples for each algorithm, which proves the theoretical calculations. Finally, they mentioned basic pieces of code that were created for the construction of the personalization system.

This thesis presents several hyperstructure-based Web search methods and a prototype system that is designed to implement the methods. Given the context of hyperlink structural and semantic information that is representable with new Web standards, this thesis is an effort to answer the open question of how to efficiently make use of such information for searching the Web and filtering and retrieving relevant information. The hyperstructure-based approach taken in this thesis is an extension to the traditional structure-based search method, which mainly handles hierarchical structures (composed by non-linking mechanisms) in structured documents (e.g., XML). In addition to such hierarchical structures, this approach can also handle both hierarchical and non-hierarchical structures composed by linking mechanisms. Compared to other link-based approaches that largely take into account the quantity of links in their search methods, this approach also makes use of the semantic information in links and link-based structures. It is in line with the trend of Web development with regard to capturing rich structural and semantic information and thereby capitalizing on the potential of new search methods. The hyperstructure-based search methods presented in this thesis can be applied to improve the search quality on the Web as the Web evolves from a poorly structured to a more structured, semantic-rich network. More concretely, by making use of hypertext composites and contexts, the search results can be more specific with respect to users’ information needs, and additionally, the users’ efforts to interpret the search results can be reduced. Presenting structured search results based on hypertext composites as inter-linked nodes/pages rather than separate nodes/pages helps users understand the retrieved information better. By making use of semantic information in hyperstructures (e.g., types of links and nodes), better filters can be developed for selecting and ranking the Web pages retrieved by search systems. These pages can be either intermediate information for further processing or final search results presented to users. By making use of domain models, domain-specific structure-based search methods can be developed, which may generate better results than general search methods that do not understand the domain-specific information.

Tese de doutoramento, Informática (Engenharia Informática), Universidade de Lisboa, Faculdade de Ciências, 2014<br>Web archives preserve information that was published on the web or digitized from printed publications. Many of that information is unique and historically valuable. However, users do not have dedicated tools to find the desired information, which hampers the usefulness of web archives. This dissertation investigates solutions towards the advance of web archive information retrieval (WAIR) and contributes to the increase of knowledge about its technology and users. The thesis underlying this work is that the search results can be improved by exploiting temporal information intrinsic to web archives. This temporal information was leveraged from two different angles. First, the long-term persistence of web documents was analyzed and modeled to better estimate their relevance to a query. Second, a temporal-dependent ranking framework that learns and combines ranking models specific for each period was devised. This approach contrasts with a typical single-model approach that ignores the variance of web characteristics over time. The proposed approach was empirically validated through various controlled experiments that demonstrated their superiority over the state-of-the-art in WAIR.<br>Os arquivos da web preservam informação que foi publicada na web ou digitalizada de publicações impressas. Muita dessa informação é única e historicamente valiosa. Contudo, os utilizadores não dispõem de ferramentas dedicadas para encontrar a informação desejada, o que limita a utilidade dos arquivos da web. Esta dissertação investiga soluções para o avanço da recuperação de informação em arquivos da web (WAIR) e contribui para o aumento de conhecimento acerca da sua tecnologia e dos seus utilizadores. A tese subjacente a este trabalho é a de que os resultados de pesquisa podem ser melhorados através da exploração de informação temporal intrínseca aos arquivos da web. Esta informação temporal foi explorada de dois ângulos diferentes. Primeiro, a longa persistência dos documentos web foi analisada e modelada para melhor estimar a relevância destes em função da pesquisa. Segundo, foi concebido um enquadramento (framework) para ordenação de resultados dependente do tempo, que aprende e combina modelos específicos para cada período. Esta abordagem contrasta com a abordagem de um modelo único que ignora a variação das características da web ao longo do tempo. A abordagem proposta foi validada empiricamente através de várias experiências controladas que demonstraram a sua superioridade em relação ao estado da arte em WAIR.

碩士<br>國立臺灣大學<br>資訊工程學研究所<br>91<br>The power of keyword-based search engines is limited by their approach. Many people have been working on developing better search methods for the Web. One major effort is the W3C Semantic Web. Semantic Web proposes the architecture of modular layers where meaningful data are encoded in RDF. Beyond the RDF layer there are more layers, such as Ontology, Rules, Logic Framework, and Proof layers. In this paper we present another framework for semantic search on the web — The Semantic Extraction, Reasoning, and Projection Framework. Our framework tries to solve this problem by providing a simple architecture in which the only layer is logic. For this, we develop a new logic language — the Path Inference Language — to extract meaningful data from XML documents, and use logic reasoning procedures to perform search in the extracted data. This approach differs from the one Semantic Web provides in several aspects. We also discuss the differences in this paper.