Relevant bibliographies by topics / World Wide Web. Search engines

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'World Wide Web. Search engines'

Author: Grafiati
Published: 4 June 2021
Last updated: 5 February 2022

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Journal articles on the topic "World Wide Web. Search engines"

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Clarke, Sarah J. "Search Engines for the World Wide Web." Journal of Internet Cataloging 2, no. 3-4 (2000): 81–93. http://dx.doi.org/10.1300/j141v02n03_06.

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Unadkat, Rimpal. "Survey Paper on Semantic Web." International Journal of Advanced Pervasive and Ubiquitous Computing 7, no. 4 (2015): 13–17. http://dx.doi.org/10.4018/ijapuc.2015100102.

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The World Wide Web (WWW) allows the people to share the information (data) from the large database repositories globally. The tremendous growth in the volume of data and with the terrific growth of number of web pages, traditional search engines now days are not appropriate and not suitable anymore. Search engine is the most important tool to discover any information in World Wide Web. Semantic Search Engine is born of traditional search engine to overcome the above problem. However, to overcome this problem in search engines to retrieve meaningful information intelligently, semantic web technologies are playing a major role. In this paper the authors present survey on the role of search engines in intelligent web, Background, Challenges and some issues.
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Leighton, H. Vernon, and Jaideep Srivastava. "First 20 precision among World Wide Web search services (search engines)." Journal of the American Society for Information Science 50, no. 10 (1999): 870–81. http://dx.doi.org/10.1002/(sici)1097-4571(1999)50:10<870::aid-asi4>3.0.co;2-g.

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Mahdi, Mohammed Najah, Abdul Rahim Ahmad, and Roslan Ismail. "Evaluating Search Results in Exploratory Search." International Journal of Engineering & Technology 7, no. 4.35 (2018): 276. http://dx.doi.org/10.14419/ijet.v7i4.35.22746.

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The volume of information available on the World Wide Web is quite significant. This plethora of information has, to a large extent constantly challenged researchers in seeking for ways of making the information easily accessible to end users in as convenient ways as possible. Characteristically, ensuring the accessibility of this large amount of information involves three all-encompassing processes of retrieval, organization and presentation. The World Wide Web offers a platform for sharing information from large database repositories globally. However, information needs to be searched with specialized tools commonly referred to as search engines. While a number of search engines does presently exist, most of these search engines are noted for their inability to retrieve information usable to the end user. It is therefore critical for the results generated from search engines to be intelligently organized for the optimal usefulness of the information to the searcher. Exploratory web technologies is capable of filing this gap. Therefore, this paper reviews exploratory search as a mechanism for conducting result-oriented search. It also reviews the ways of evaluating the search results obtained from an exploratory search.
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Qian, Shuang Yan. "Design and Implementation of Landscape Plant Information Search Engine." Advanced Materials Research 971-973 (June 2014): 1892–96. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.1892.

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With the explosive growth of the World Wide Web information, we need the appropriate retrieval tools, especially the retrieval of the professional information, we need a embody of search engines with the professional vocabulary features. Based on the research of search engine's core technology, this paper presents a design scheme which is the botanical garden plant information search engine based on Internet data, we descript of its design.
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T, Anuradha, and Tayyaba Nousheen. "MACHINE LEARNING BASED SEARCH ENGINE WITH CRAWLING, INDEXING AND RANKING." International Journal of Computer Science and Mobile Computing 10, no. 7 (2021): 76–83. http://dx.doi.org/10.47760/ijcsmc.2021.v10i07.011.

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The web is the heap and huge collection of wellspring of data. The Search Engine are used for retrieving the information from World Wide Web (WWW). Search Engines are helpful for searching user keywords and provide the accurate result in fraction of seconds. This paper proposed Machine Learning based search engine which will give more relevant user searches in the form of web pages. To display the user entered query search engine plays a major role of basic interface. Every site comprises of the heaps of site pages that are being made and sent on the server.
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Milonas, Elizabeth. "Wittgenstein and web facets." NASKO 3, no. 1 (2011): 33. http://dx.doi.org/10.7152/nasko.v3i1.12788.

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The World Wide Web has grown exponentially in the last few years. The popularity of Web search engines has also grown in a similar manner. The task of a Web search engine is to provide the Web searcher with accurate and targeted information from the plethora of information available on the Web. This is a daunting task that requires the careful usage of language to ensure accuracy. As a result, the importance of the usage and meaning of language in the Web domain has become the focus of recent research. In this paper, the author will explore Wittgenstein’s later philosophy of language as it applies to the language used in the search result pages of a Web search engine in an effort to broaden the understanding of language usage within this domain.
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Sharma, Dilip Kumar, and A. K. Sharma. "Search Engine." International Journal of Information Communication Technologies and Human Development 3, no. 2 (2011): 38–51. http://dx.doi.org/10.4018/ijicthd.2011040103.

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ICT plays a vital role in human development through information extraction and includes computer networks and telecommunication networks. One of the important modules of ICT is computer networks, which are the backbone of the World Wide Web (WWW). Search engines are computer programs that browse and extract information from the WWW in a systematic and automatic manner. This paper examines the three main components of search engines: Extractor, a web crawler which starts with a URL; Analyzer, an indexer that processes words on the web page and stores the resulting index in a database; and Interface Generator, a query handler that understands the need and preferences of the user. This paper concentrates on the information available on the surface web through general web pages and the hidden information behind the query interface, called deep web. This paper emphasizes the Extraction of relevant information to generate the preferred content for the user as the first result of his or her search query. This paper discusses the aspect of deep web with analysis of a few existing deep web search engines.
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Feeney, Kathleen. "Retrieval of Archival Finding Aids Using World-Wide-Web Search Engines." American Archivist 62, no. 2 (1999): 206–28. http://dx.doi.org/10.17723/aarc.62.2.g220803l05v4l643.

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Li, Keqin. "Optimal Allocation Of Heterogeneous Robots In World Wide Web Search Engines." International Journal of Computer Mathematics 80, no. 8 (2003): 945–56. http://dx.doi.org/10.1080/0020716031000112349.

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

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Chakravarty, Rupak, and Sukhwinder Randhawa. "ACADEMIC SEARCH ENGINES: LIBRARIAN'S FRIEND,RESEARCHER'S DELIGHT." INFLIBNET Centre, 2006. http://hdl.handle.net/10150/105232.

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Search engines are about excitement, optimism, hope and enrichment. Search engines are also about despair and disappointment. A researcher while using search engines for resource discovery might have experienced one or the other sentiments. One may say that user satisfaction depends much upon the search strategies deployed by the user. But at the same time its also depends upon the quality of search engine used for information retrieval. Today, there are many search engines used for resource discovery. They display the results of the searches made in readily-comprehensible manner with lots of customization possibilities including refining and sorting. This paper is an attempt to analyze qualitatively and quantitatively the three most used and popular search engines for academic resource discovery: Google Scholar, Scirus and Windows Live Academic.
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Lewandowski, Dirk. "Web Searching, Search Engines and Information Retrieval." ISO Press, 2005. http://hdl.handle.net/10150/106395.

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This article discusses Web search engines; mainly the challenges in indexing the World Wide Web, the user behaviour, and the ranking factors used by these engines. Ranking factors are divided into query-dependent and query-independent factors, the latter of which have become more and more important within recent years. The possibilities of these factors are limited, mainly of those that are based on the widely used link popularity measures. The article concludes with an overview of factors that should be considered to determine the quality of Web search engines.
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Selberg, Erik Warren. "Towards comprehensive Web search /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/6873.

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Hicks, Janette M. "Search algorithms for discovery of Web services." Diss., Online access via UMI:, 2005. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:1425747.

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Young, Joel D. "Exploiting the structure of the web for spidering /." View online version; access limited to Brown University users, 2005. http://wwwlib.umi.com/dissertations/fullcit/3174706.

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Blaauw, Pieter. "Search engine poisoning and its prevalence in modern search engines." Thesis, Rhodes University, 2013. http://hdl.handle.net/10962/d1002037.

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The prevalence of Search Engine Poisoning in trending topics and popular search terms on the web within search engines is investigated. Search Engine Poisoning is the act of manipulating search engines in order to display search results from websites infected with malware. Research done between February and August 2012, using both manual and automated techniques, shows us how easily the criminal element manages to insert malicious content into web pages related to popular search terms within search engines. In order to provide the reader with a clear overview and understanding of the motives and the methods of the operators of Search Engine Poisoning campaigns, an in-depth review of automated and semi-automated web exploit kits is done, as well as looking into the motives for running these campaigns. Three high profile case studies are examined, and the various Search Engine Poisoning campaigns associated with these case studies are discussed in detail to the reader. From February to August 2012, data was collected from the top trending topics on Google’s search engine along with the top listed sites related to these topics, and then passed through various automated tools to discover if these results have been infiltrated by the operators of Search Engine Poisoning campaings, and the results of these automated scans are then discussed in detail. During the research period, manual searching for Search Engine Poisoning campaigns was also done, using high profile news events and popular search terms. These results are analysed in detail to determine the methods of attack, the purpose of the attack and the parties behind it
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Kruger, Andries F. "Machine learning, data mining, and the World Wide Web : design of special-purpose search engines." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53492.

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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.
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Zamir, Oren Eli. "Clustering web documents : a phrase-based method for grouping search engine results /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/6884.

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Knopke, Ian. "Building a search engine for music and audio on the World Wide Web." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85177.

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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.
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Grewal, Ratvinder Singh. "A visual metaphor-based tool for a search-engine user interface." Thesis, University of Wolverhampton, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.272531.

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Books on the topic "World Wide Web. Search engines"

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Emily, Glossbrenner, ed. Search engines for the World Wide Web. 3rd ed. Peachpit Press, 2001.

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Emily, Glossbrenner, ed. Search engines for the World Wide Web. 2nd ed. Peachpit Press, 1999.

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Emily, Glossbrenner, ed. Search engines for the World Wide Web. Peachpit Press, 1998.

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Maze, Susan. Authoritative guide to Web search engines. Neal-Schuman, 1997.

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Hill, Brad. World Wide Web searching for dummies. 2nd ed. IDG Books Worldwide, 1997.

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World Wide Web searching for dummies. IDG Books Worldwide, 1996.

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Sudatta, Chowdhury, ed. Information sources and searching on the World Wide Web. Library Association Pub., 2001.

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1975-, Macinta Tim, ed. Web developer.com guide to search engines. J. Wiley, 1998.

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Pfaffenberger, Bryan. Web search strategies. MIS Press, 1996.

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Web search garage. Prentice Hall PTR, 2004.

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Book chapters on the topic "World Wide Web. Search engines"

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Chang, George, Marcus J. Healey, James A. M. McHugh, and Jason T. L. Wang. "Multimedia Search Engines." In Mining the World Wide Web. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1639-2_4.

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Chang, George, Marcus J. Healey, James A. M. McHugh, and Jason T. L. Wang. "Keyword-Based Search Engines." In Mining the World Wide Web. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1639-2_1.

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Marchiori, Massimo. "Security of World Wide Web Search Engines." In Reliability, Quality and Safety of Software-Intensive Systems. Springer US, 1997. http://dx.doi.org/10.1007/978-0-387-35097-4_13.

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Chang, George, Marcus J. Healey, James A. M. McHugh, and Jason T. L. Wang. "Query-Based Search Systems." In Mining the World Wide Web. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1639-2_2.

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Balog, Krisztian, Leif Azzopardi, and Maarten de Rijke. "Resolving Person Names in Web People Search." In Weaving Services and People on the World Wide Web. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00570-1_15.

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Buehrer, Greg, Jack W. Stokes, Kumar Chellapilla, and John C. Platt. "Classification of Automated Search Traffic." In Weaving Services and People on the World Wide Web. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00570-1_1.

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Milic-Frayling, Natasa. "World Wide Web Challenges: Supporting Users in Search and Navigation." In SOFSEM 2004: Theory and Practice of Computer Science. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24618-3_5.

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Dreger, M., S. Lohrum, H. Schweppe, and C. D. Ziegler. "Ariadne, an interactive navigation and search system for computer science information on the world-wide web." In Digital Libraries in Computer Science: The MeDoc Approach. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0052519.

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Frost, Fraser L. "Towards an Understanding of Internal and External Search for Purchase Decisions involving the World Wide Web." In Global Perspectives in Marketing for the 21st Century. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17356-6_78.

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"Working with the search engines." In World Wide Web. Routledge, 2003. http://dx.doi.org/10.4324/9780203402962-12.

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Conference papers on the topic "World Wide Web. Search engines"

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Peng, Qian, Weiyi Meng, Hai He, and Clement Yu. "Clustering e-commerce search engines." In the 13th international World Wide Web conference. ACM Press, 2004. http://dx.doi.org/10.1145/1013367.1013503.

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Lam, Ka Wai, and Chi Ho Leung. "Rank aggregation for meta-search engines." In the 13th international World Wide Web conference. ACM Press, 2004. http://dx.doi.org/10.1145/1013367.1013487.

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Li, Lihong, Shunbao Chen, Jim Kleban, and Ankur Gupta. "Counterfactual Estimation and Optimization of Click Metrics in Search Engines." In WWW '15: 24th International World Wide Web Conference. ACM, 2015. http://dx.doi.org/10.1145/2740908.2742562.

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Agrawal, Rakesh, Behzad Golshan, and Evangelos Papalexakis. "A Study of Distinctiveness in Web Results of Two Search Engines." In WWW '15: 24th International World Wide Web Conference. ACM, 2015. http://dx.doi.org/10.1145/2740908.2743060.

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Blanco, Roi, Matteo Catena, and Nicola Tonellotto. "Exploiting Green Energy to Reduce the Operational Costs of Multi-Center Web Search Engines." In WWW '16: 25th International World Wide Web Conference. International World Wide Web Conferences Steering Committee, 2016. http://dx.doi.org/10.1145/2872427.2883021.

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Robertson, Ronald E., David Lazer, and Christo Wilson. "Auditing the Personalization and Composition of Politically-Related Search Engine Results Pages." In the 2018 World Wide Web Conference. ACM Press, 2018. http://dx.doi.org/10.1145/3178876.3186143.

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Ding, Dawei, Jun Yang, Qing Li, Liping Wang, and Liu Wenyin. "Towards a flash search engine based on expressive semantics." In the 13th international World Wide Web conference. ACM Press, 2004. http://dx.doi.org/10.1145/1013367.1013531.

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Azimi, Javad, Adnan Alam, and Ruofei Zhang. "Ads Keyword Rewriting Using Search Engine Results." In WWW '15: 24th International World Wide Web Conference. ACM, 2015. http://dx.doi.org/10.1145/2740908.2742739.

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Sazoglu, Fethi Burak, Özgür Ulusoy, Ismail Sengor Altingovde, Rifat Ozcan, and Berkant Barla Cambazoglu. "Propagating Expiration Decisions in a Search Engine Result Cache." In WWW '15: 24th International World Wide Web Conference. ACM, 2015. http://dx.doi.org/10.1145/2740908.2742772.

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Soldaini, Luca, and Elad Yom-Tov. "Inferring Individual Attributes from Search Engine Queries and Auxiliary Information." In WWW '17: 26th International World Wide Web Conference. International World Wide Web Conferences Steering Committee, 2017. http://dx.doi.org/10.1145/3038912.3052629.

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