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Journal articles on the topic 'Web Search engines'

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Published: 4 June 2021
Last updated: 30 July 2024

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1

Rajashekar, T. B. "Web search engines." Resonance 3, no. 11 (November 1998): 40–53. http://dx.doi.org/10.1007/bf02838708.

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Schwartz, Candy. "Web search engines." Journal of the American Society for Information Science 49, no. 11 (1998): 973–82. http://dx.doi.org/10.1002/(sici)1097-4571(1998)49:11<973::aid-asi3>3.0.co;2-z.

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Duka, Mariusz, Marek Sikora, and Artur Strzelecki. "From Web Catalogs to Google: A Retrospective Study of Web Search Engines Sustainable Development." Sustainability 15, no. 8 (April 17, 2023): 6768. http://dx.doi.org/10.3390/su15086768.

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This study presents a review of search engines and search engine optimization and shows how the search engine landscape relates to sustainable development. We have used a narrative review research method and described three main topics: the past and present of web catalogs and search engines; current knowledge about the dominant types of search results presented in Google search; and methods of search engine optimization. Technical elements of important website areas related to technical website auditing are discussed. We summarize our research with several key findings on how web search engines are involved in sustainable development and offer a glimpse into the future use of web searching with the help of artificial intelligence chats and prompt engineering.
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Bukhor, Saiful i. "Analisis Perbandingan Fitur Search Engine." INFORMAL: Informatics Journal 3, no. 1 (February 25, 2019): 17. http://dx.doi.org/10.19184/isj.v3i1.9850.

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Search engines are used in the web as a tool for information retrieval. Web Server is a large warehouse of heterogeneous and unstructured data so that to filter out relevant information from people, a search engine is needed. Search engines usually consist of page repositories, indexing modules, query modules and ranking modules. Search engines do not work alone, besides that there is a web browser that supports the work of this search engine to be more optimal. A browser is software that is run on a user's computer (user) that displays web documents or information taken from a web server [1]. A browser is the type of intermediary the user uses most often. This paper aims to analyze three search engines namely Google, Yahoo, and Bing based on existing features. These features include web search, image search, video search, news search, route search, book search, change search settings, display number of views, shopping, language translator. Google stands as the best search engine among all search engines, which works using the Page Rank algorithm. Page Rank is a numerical value that determines the importance of a web page by calculating the number of backlinks.
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Unadkat, Rimpal. "Survey Paper on Semantic Web." International Journal of Advanced Pervasive and Ubiquitous Computing 7, no. 4 (October 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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Heintz, Christophe. "Web search engines and distributed assessment systems." Distributed Cognition 14, no. 2 (September 21, 2006): 387–409. http://dx.doi.org/10.1075/pc.14.2.15hei.

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I analyse the impact of search engines on our cognitive and epistemic practices. For that purpose, I describe the processes of assessment of documents on the Web as relying on distributed cognition. Search engines together with Web users, are distributed assessment systems whose task is to enable efficient allocation of cognitive resources of those who use search engines. Specifying the cognitive function of search engines within these distributed assessment systems allows interpreting anew the changes that have been caused by search engine technologies. I describe search engines as implementing reputation systems and point out the similarities with other reputation systems. I thus call attention to the continuity in the distributed cognitive processes that determine the allocation of cognitive resources for information gathering from others.
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Kasavana, Michael L., and Carl P. Borchgrevink. "Untangling Web Search Engines." Journal of Hospitality & Tourism Education 10, no. 4 (January 1999): 45–51. http://dx.doi.org/10.1080/10963758.1999.10685210.

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Alqaaidi, Sakher Khalil. "A Hybrid Approach for Web Change Detection." International Journal of Information Technology and Web Engineering 8, no. 2 (April 2013): 46–69. http://dx.doi.org/10.4018/jitwe.2013040104.

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Search engines save copies of crawled web pages to provide instant search results, saved pages may become old and un-updated as original pages change providing new information and new links, and most of websites don’t submit these new changes to search engines so search engines don’t depend mainly on websites techniques of submitting changes. Keeping pages fresh and updated in search engine is important for giving real page ranks and for providing real time information. Techniques were invented to improve the page update process by search engine. In this paper the author combines two of good known techniques and implements the new one via experiments that improve better results in different experiment cases.
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Stevenson, Valerie. "Search Engine Update." Legal Information Management 1, no. 3 (2001): 28–31. http://dx.doi.org/10.1017/s1472669600000566.

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Looking back to 1999, there were a number of search engines which performed equally well. I recommended defining the search strategy very carefully, using Boolean logic and field search techniques, and always running the search in more than one search engine. Numerous articles and Web columns comparing the performance of different search engines came to different conclusions on the ‘best’ search engines. Over the last year, however, all the speakers at conferences and seminars I have attended have recommended Google as their preferred tool for locating all kinds of information on the Web. I confess that I have now abandoned most of my carefully worked out search strategies and comparison tests, and use Google for most of my own Web searches.
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Kumar, Kailash, and Abdulaziz Al-Besher. "Critical Analysis of Major Search Engines." Journal of Computational and Theoretical Nanoscience 16, no. 9 (September 1, 2019): 3712–16. http://dx.doi.org/10.1166/jctn.2019.8239.

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This paper examines the overlapping of the results retrieved between three major search engines namely Google, Yahoo and Bing. A rigorous analysis of overlap among these search engines was conducted on 100 random queries. The overlap of first ten web page results, i.e., hundred results from each search engine and only non-sponsored results from these above major search engines were taken into consideration. Search engines have their own frequency of updates and ranking of results based on their relevance. Moreover, sponsored search advertisers are different for different search engines. Single search engine cannot index all Web pages. In this research paper, the overlapping analysis of the results were carried out between October 1, 2018 to October 31, 2018 among these major search engines namely, Google, Yahoo and Bing. A framework is built in Java to analyze the overlap among these search engines. This framework eliminates the common results and merges them in a unified list. It also uses the ranking algorithm to re-rank the search engine results and displays it back to the user.
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MARCHIORI, MASSIMO. "SOCIAL SEARCH ENGINES." International Journal of Bifurcation and Chaos 17, no. 07 (July 2007): 2355–61. http://dx.doi.org/10.1142/s0218127407018440.

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The web landscape has undergone massive changes in the past years. On the other hand, search engine technology has not quite kept the same pace. In this article we look at the current scenarios, and argue how social flows can be used to make up for a better generation of search engines. We consider how society and technological progress somehow changed the rules of the game, introducing good but also bad components, and see how this situation could be modeled by search engines. Along this line of thinking, we show how the real components of interest are not just web pages, but flows of information of any kind, that need to be merged: this opens up for a wide range of improvements and far-looking developments, towards a new horizon of social search.
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Marrón, David González, Verónica Paola Corona Ramírez, Juan Alejandro Arrieta Zuñiga, and Roberto Hernández Pérez. "Techniques to improve web sites positioning in the World Wide Web." South Florida Journal of Development 5, no. 1 (January 16, 2024): 254–64. http://dx.doi.org/10.46932/sfjdv5n1-019.

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In this computer's era, characterized by the rapid proliferation of indexed documents across the World Wide Web, the imperative arises for the employment of diverse strategies to enhance the positioning of websites within search engines, including but not limited to Google, Yahoo, and Bing. The voluminous expanse of indexed documents on the web, exceeding 30 billion, underscores the need for a systematic approach. This paper introduces the Search Engine Optimization (SEO) technique a method designed to elevate the inherent attributes of websites, facilitating superior evaluation and ranking by search engines, Notably, search engines incorporate over 200 distinct features within their ranking algorithms, encompassing internal factors inherent to developed websites and external factors predominantly associated with usage frequency. This paper details the series of activities related to the SEO technique, as well as the measurement results obtained before and after its application.
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Arunachalam, N., S. Radjou, P. Aravindan, and T. Sivagurunathan. "Privacy Proliferation of Customized Web Search Engine." International Journal of Engineering & Technology 7, no. 2.32 (May 31, 2018): 150. http://dx.doi.org/10.14419/ijet.v7i2.32.15391.

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In last few years the illegal disclosure of user privacy in web search engine has become more serious. Protecting and Pre-venting user privacy from illegal disclosure is attracting the interest among researchers in recent times. Existing web search engines do not consider the privacy of the users. Search engines tend to collect all the information from the user. A system to ensure the privacy of the user is essential. Hence, the Personalized Web Search (PWS) method was put forward to take control over the amount of information that the user can provide to the search engines. This PWS provides privacy protec-tion in web search system and minimize the information disclosure of the user related to privacy through a customizable web-search.
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Colaric, Susan M. "Instruction for Web Searching: An Empirical Study." College & Research Libraries 64, no. 2 (March 1, 2003): 111–22. http://dx.doi.org/10.5860/crl.64.2.111.

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Users searching the Web have difficulty using search engines and developing queries. Searches tend to be simple, and Boolean operators are used infrequently and incorrectly. Users also are unaware that search engines operate differently from other information retrieval systems. Yet, there is little research on effective instructional methods for teaching users how to search the Web. Research has looked at instructional methods for other types of information retrieval, but these systems differ a great deal from the Web. The purpose of this study was to determine what undergraduate students know about search engines and to examine instructional treatments to aid searchers in using a search engine.
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RAKHSHAN, ARASH, LAWRENCE B. HOLDER, and DIANE J. COOK. "STRUCTURAL WEB SEARCH ENGINE." International Journal on Artificial Intelligence Tools 13, no. 01 (March 2004): 27–44. http://dx.doi.org/10.1142/s0218213004001405.

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We present a new approach in web search engines. The web creates new challenges for information retrieval. The vast improvement in information access is not the only advantage resulting from the keyword search. Additionally, much potential exists for analyzing interests and relationships within the structure of the web. The creation of a hyperlink by the author of a web page explicitly represents a relationship between the source and destination pages which demonstrates the hyperlink structure between web pages. Our web search engine searches not only for the keywords in the web pages, but also for the hyperlink structure between them. Comparing the results of structural web search versus keyword-based search indicates an improved ability to access desired information. We also discuss steps toward mining the queries input to the structural web search engine.
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O’Neill, Stephen, and Kevin Curran. "The Core Aspects of Search Engine Optimisation Necessary to Move up the Ranking." International Journal of Ambient Computing and Intelligence 3, no. 4 (October 2011): 62–70. http://dx.doi.org/10.4018/jaci.2011100105.

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Search engine optimization (SEO) is the process of improving the visibility, volume and quality of traffic to website or a web page in search engines via the natural search results. SEO can also target other areas of a search, including image search and local search. SEO is one of many different strategies used for marketing a website but SEO has been proven the most effective. An Internet marketing campaign may drive organic search results to websites or web pages but can be involved with paid advertising on search engines. All search engines have a unique way of ranking the importance of a website. Some search engines focus on the content while others review Meta tags to identify who and what a web site’s business is. Most engines use a combination of Meta tags, content, link popularity, click popularity and longevity to determine a sites ranking. To make it even more complicated, they change their ranking policies frequently. This paper provides an overview of search engine optimisation strategies and pitfalls.
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Norouzi, Yaghoub, and Hoda Homavandi. "Image search and retrieval problems in web search engines." Online Information Review 42, no. 6 (October 8, 2018): 752–67. http://dx.doi.org/10.1108/oir-01-2017-0007.

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PurposeThe purpose of this paper is to investigate image search and retrieval problems in selected search engines in relation to Persian writing style challenges.Design/methodology/approachThis study is an applied one, and to answer the questions the authors used an evaluative research method. The aim of the research is to explore the morphological and semantic problems of Persian language in connection with image search and retrieval among the three major and widespread search engines: Google, Yahoo and Bing. In order to collect the data, a checklist designed by the researcher was used and then the data were analyzed by descriptive and inferential statistics.FindingsThe results indicate that Google, Yahoo and Bing search engines do not pay enough attention to morphological and semantic features of Persian language in image search and retrieval. This research reveals that six groups of Persian language features include derived words, derived/compound words, Persian and Arabic Plural words, use of dotted T and the use of spoken language and polysemy, which are the major problems in this area. In addition, the results suggest that Google is the best search engine of all in terms of compatibility with Persian language features.Originality/valueThis study investigated some new aspects of the above-mentioned subject through combining morphological and semantic aspects of Persian language with image search and retrieval. Therefore, this study is an interdisciplinary research, the results of which would help both to offer some solutions and to carry out similar research on this subject area. This study will also fill a gap in research studies conducted so far in this area in Farsi language, especially in image search and retrieval. Moreover, findings of this study can help to bridge the gap between the user’s questions and search engines (systems) retrievals. In addition, the methodology of this paper provides a framework for further research on image search and retrieval in databases and search engines.
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Beneventano, Domenico, and Sonia Bergamaschi. "Provenance-Aware Semantic Search Engines Based On Data Integration Systems." International Journal of Organizational and Collective Intelligence 4, no. 2 (April 2014): 1–30. http://dx.doi.org/10.4018/ijoci.2014040101.

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Search engines are common tools for virtually every user of the Internet and companies, such as Google and Yahoo!, have become household names. Semantic Search Engines try to augment and improve traditional Web Search Engines by using not just words, but concepts and logical relationships. Given the openness of the Web and the different sources involved, a Web Search Engine must evaluate quality and trustworthiness of the data; a common approach for such assessments is the analysis of the provenance of information. In this paper a relevant class of Provenance-aware Semantic Search Engines, based on a peer-to-peer, data integration mediator-based architecture is described. The architectural and functional features are an enhancement with provenance of the SEWASIE semantic search engine developed within the IST EU SEWASIE project, coordinated by the authors. The methodology to create a two level ontology and the query processing engine developed within the SEWASIE project, together with provenance extension are fully described.
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Kerkmann, Friederike, and Dirk Lewandowski. "Accessibility of web search engines." Library Review 61, no. 8/9 (August 31, 2012): 608–21. http://dx.doi.org/10.1108/00242531211292105.

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Henzinger, Monika R., Rajeev Motwani, and Craig Silverstein. "Challenges in web search engines." ACM SIGIR Forum 36, no. 2 (September 2002): 11–22. http://dx.doi.org/10.1145/792550.792553.

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Risvik, Knut Magne, and Rolf Michelsen. "Search engines and Web dynamics." Computer Networks 39, no. 3 (June 2002): 289–302. http://dx.doi.org/10.1016/s1389-1286(02)00213-x.

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Hawking, D. "Web Search Engines: Part 1." Computer 39, no. 6 (June 2006): 86–88. http://dx.doi.org/10.1109/mc.2006.213.

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Hawking, D. "Web Search Engines: Part 2." Computer 39, no. 8 (August 2006): 88–90. http://dx.doi.org/10.1109/mc.2006.286.

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Santos, Rodrygo L. T., Craig Macdonald, and Iadh Ounis. "Mimicking Web search engines for expert search." Information Processing & Management 47, no. 4 (July 2011): 467–81. http://dx.doi.org/10.1016/j.ipm.2010.11.009.

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Kanavos, Andreas, Christos Makris, Yannis Plegas, and Evangelos Theodoridis. "Ranking Web Search Results Exploiting Wikipedia." International Journal on Artificial Intelligence Tools 25, no. 03 (June 2016): 1650018. http://dx.doi.org/10.1142/s0218213016500184.

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It is widely known that search engines are the dominating tools for finding information on the web. In most of the cases, these engines return web page references on a global ranking taking in mind either the importance of the web site or the relevance of the web pages to the identified topic. In this paper, we focus on the problem of determining distinct thematic groups on web search engine results that other existing engines provide. We additionally address the problem of dynamically adapting their ranking according to user selections, incorporating user judgments as implicitly registered in their selection of relevant documents. Our system exploits a state of the art semantic web data mining technique that identifies semantic entities of Wikipedia for grouping the result set in different topic groups, according to the various meanings of the provided query. Moreover, we propose a novel probabilistic Network scheme that employs the aforementioned topic identification method, in order to modify ranking of results as the users select documents. We evaluated in practice our implemented prototype with extensive experiments with the ClueWeb09 dataset using the TREC’s 2009, 2010, 2011 and 2012 Web Tracks’ where we observed improved retrieval performance compared to current state of the art re-ranking methods.
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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 (April 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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Seymour, Tom, Dean Frantsvog, and Satheesh Kumar. "History Of Search Engines." International Journal of Management & Information Systems (IJMIS) 15, no. 4 (September 12, 2011): 47. http://dx.doi.org/10.19030/ijmis.v15i4.5799.

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As the number of sites on the Web increased in the mid-to-late 90s, search engines started appearing to help people find information quickly. Search engines developed business models to finance their services, such as pay per click programs offered by Open Text in 1996 and then Goto.com in 1998. Goto.com later changed its name to Overture in 2001, and was purchased by Yahoo! in 2003, and now offers paid search opportunities for advertisers through Yahoo! Search Marketing. Google also began to offer advertisements on search results pages in 2000 through the Google Ad Words program. By 2007, pay-per-click programs proved to be primary money-makers for search engines. In a market dominated by Google, in 2009 Yahoo! and Microsoft announced the intention to forge an alliance. The Yahoo! & Microsoft Search Alliance eventually received approval from regulators in the US and Europe in February 2010. Search engine optimization consultants expanded their offerings to help businesses learn about and use the advertising opportunities offered by search engines, and new agencies focusing primarily upon marketing and advertising through search engines emerged. The term "Search Engine Marketing" was proposed by Danny Sullivan in 2001 to cover the spectrum of activities involved in performing SEO, managing paid listings at the search engines, submitting sites to directories, and developing online marketing strategies for businesses, organizations, and individuals. Some of the latest theoretical advances include Search Engine Marketing Management (SEMM). SEMM relates to activities including SEO but focuses on return on investment (ROI) management instead of relevant traffic building (as is the case of mainstream SEO). SEMM also integrates organic SEO, trying to achieve top ranking without using paid means of achieving top in search engines, and PayPerClick SEO. For example some of the attention is placed on the web page layout design and how content and information is displayed to the website visitor.
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P, Dr Natarajan, and Sonali Pandey. "INFORMATION RETRIEVAL AND WEB SEARCH." International Research Journal of Computer Science 8, no. 8 (August 30, 2021): 215–20. http://dx.doi.org/10.26562/irjcs.2021.v0808.010.

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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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Zuo, Xiang Lin, Wen Bo Wang, Ying Wang, and Wan Li Zuo. "Research and Implementation of Improved Real-Time Crawler Modeling." Applied Mechanics and Materials 312 (February 2013): 791–95. http://dx.doi.org/10.4028/www.scientific.net/amm.312.791.

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The past decade has witnessed the rapid development of search engines, which has become an indispensable part of everyday life. However, people are no longer satisfied with accessing to ordinary information, and they may instead pay more attention to fresh information. This demand poses challenges to traditional search engines, which concern more about relevance and importance of web pages. A search engine compresses three modules: crawler, indexer and searcher. Changes are needed for all these three parts to improve search engine's freshness. This paper investigates the first part of search engine crawler, we analyze the requirements for real-time crawler, and propose a novel real-time crawler based on more accurate estimation of refresh time. Experimental results demonstrate that the proposed real-time crawler can help search engine improve its freshness.
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Jha, Radhika. "Xperia Search Engine." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (May 31, 2023): 6331–40. http://dx.doi.org/10.22214/ijraset.2023.52996.

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Abstract: This research paper delves into the innerworkings of search engines and introduces Xperia, a personalized search engine aimed at enhancing information retrieval. The paper explores the fundamentaltechnologies employed by search engines, tracing their evolution and growth over time. It presents the development and implementation of Xperia, highlighting its unique feature set that goes beyond traditional search engines by providing users with not only relevant resourcelinks but also extracted information from various web sources. The paper begins with an introduction, providing the background and motivation for the research, as well as outlining the research objectives and scope. It then delves into the fundamentals of search engines, discussing their components, crawling and indexing processes, ranking algorithms, and user interfaces. The evolution of search engine technologies is examined, from the early stages to the current advancements in semantic search, natural language processing, and the incorporation of machine learning and artificial intelligence.
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Prokoph, Andreas. "Search Integration with WebSphere Portal." International Journal of Web Portals 2, no. 3 (July 2010): 1–18. http://dx.doi.org/10.4018/jwp.2010070101.

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Modern web applications and servers like Portal require adequate support for integration of search services due to user focused information delivery and user interaction, as well as new technologies used to render such information, which is exemplified by two fundamental problems that have long plagued web crawlers: dynamic content and Javascript generated content. Today, the solution is simple: ignore such web pages. To enable “search” in Portals, a different “crawling” paradigm is required to search engines to gather and consume information. WebSphere Portal provides a framework that propagates content and information through “Seedlists”—comparable to HTML based sitemaps but richer in terms of features. This mandates that information and content delivering applications must be “search engine aware”, requiring them to enable services and seedlists for fast, efficient and complete delivery of content and information. This is the main integration point for search engines into the portal for Portal site search services for a rich and user focused search experience. This article discusses how such technologies can allow for more efficient crawling of public Portal sites by prominent Internet search engines as well as myths surrounding search engine optimization.
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Hughes, Emma. "Web Search Engines - Not Yet a Reliable Replacement for Bibliographic Databases." Evidence Based Library and Information Practice 13, no. 3 (September 13, 2018): 85–87. http://dx.doi.org/10.18438/eblip29378.

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A Review of: Bates, J., Best, P., McQuilkin, J., & Taylor, B. (2017) Will web search engines replace bibliographic databases in the systematic identification of research? The Journal of Academic Librarianship, 43(1), 8-17. https://doi.org/10.1016/j.acalib.2016.11.003 Abstract Objective - To explore whether web search engines could replace bibliographic databases in retrieving research. Design - Systematic review. Setting - English language articles in health and social care; comparing bibliographic databases and web search engines for retrieving research published between January 2005 and August 2015, in peer-reviewed journals and available in full-text. Subjects - Eight bibliographic databases: ASSIA (Applied Social Sciences Index and Abstracts), CINAHL Plus (Cumulative Index to Nursing and Allied Health Literature), LISA (Library and Information Science Abstracts), Medline, PsycInfo, Scopus, SSA (Social Services Abstracts), and SSCI (Social Sciences Citation Index) and five web search engines: Ask, Bing, Google, Google Scholar, Yahoo. Methods - A literature search via the above bibliographic databases and web search engines. The retrieved results were independently appraised by two researchers, using a combination of tools and checklists, including the PRESS checklist (McGowan et al., 2016) and took guidance on developing search strategies from the Centre for Reviews and Dissemination (2009). Main Results - Sixteen papers met the appraisal requirements. Each paper compared at least one bibliographic database against one web-search engine. The authors also discuss findings from their own search process. Precision and sensitivity scores from each paper were compared. The results highlighted that web search engines do not necessarily use Boolean logic and in general have limited functionality compared to bibliographic databases. There were variances in the way precision scores were calculated between papers, but when based on the first 100 results, web search engines were similar to some databases. However, their sensitivity scores were much weaker. Conclusion - Whilst precision scores were strong for web search engines, sensitivity was lacking; therefore web search engines cannot be seen as a replacement for bibliographic databases at this time. The authors recommend improving the quality of reporting in studies regarding literature searching in academia in order for reliable comparisons to be made.
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Hook, David. "Study of Search Engine Transaction Logs Shows Little Change in How Users use Search Engines." Evidence Based Library and Information Practice 1, no. 3 (September 14, 2006): 67. http://dx.doi.org/10.18438/b80014.

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A review of: Jansen, Bernard J., and Amanda Spink. “How Are We Searching the World Wide Web? A Comparison of Nine Search Engine Transaction Logs.” Information Processing & Management 42.1 (2006): 248-263. Objective – To examine the interactions between users and search engines, and how they have changed over time. Design – Comparative analysis of search engine transaction logs. Setting – Nine major analyses of search engine transaction logs. Subjects – Nine web search engine studies (4 European, 5 American) over a seven-year period, covering the search engines Excite, Fireball, AltaVista, BWIE and AllTheWeb. Methods – The results from individual studies are compared by year of study for percentages of single query sessions, one-term queries, operator (and, or, not, etc.) usage and single result page viewing. As well, the authors group the search queries into eleven different topical categories and compare how the breakdown has changed over time. Main Results – Based on the percentage of single query sessions, it does not appear that the complexity of interactions has changed significantly for either the U.S.-based or the European-based search engines. As well, there was little change observed in the percentage of one-term queries over the years of study for either the U.S.-based or the European-based search engines. Few users (generally less than 20%) use Boolean or other operators in their queries, and these percentages have remained relatively stable. One area of noticeable change is in the percentage of users viewing only one results page, which has increased over the years of study. Based on the studies of the U.S.-based search engines, the topical categories of ‘People, Place or Things’ and ‘Commerce, Travel, Employment or Economy’ are becoming more popular, while the categories of ‘Sex and Pornography’ and ‘Entertainment or Recreation’ are declining. Conclusions – The percentage of users viewing only one results page increased during the years of the study, while the percentages of single query sessions, one-term sessions and operator usage remained stable. The increase in single result page viewing implies that users are tending to view fewer results per web query. There was also a significant difference in the percentage of queries using Boolean operators between the US-based and the European-based search engines. One of the study’s findings was that results from a study of a particular search engine cannot necessarily be applied to all search engines. Finally, web search topics show a trend towards information or commerce searching rather than entertainment.
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Al-anbaki, Simaa Hassan Hadi. "Smart Search Engine." International Academic Journal of Science and Engineering 11, no. 1 (June 5, 2024): 317–21. http://dx.doi.org/10.9756/iajse/v11i1/iajse1137.

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Existing information retrieval systems, such search engines, must be improved due to the issue of having too much information on the web or in broad sectors. More consideration is needed. Integrated search tools that can manage searches and filters effectively and show relevant results The main sitting technology is bloated with ever-increasing volumes of data, much like the Internet. You'll have finished your keyword research and all of this information one day. Its capacity to deliver timely information that people are seeking. Search engines work to overcome the restrictions imposed by the conventional method of keyword research as a result. This study seeks to outline the primary issues that keyword search engines currently face in order to keep up with the rapid expansion of the web and to meet all user expectations in a timely manner. In the next section, it examines a number of models that are not dependent on keywords that have been created, created, or used by researchers and search engines, and rates those technologies in accordance with the aspects that each search engine prioritizes in order to deliver results.
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Bello, Rotimi-Williams, and Firstman Noah Otobo. "Conversion of Website Users to Customers-The Black Hat SEO Technique." International Journal of Advanced Research in Computer Science and Software Engineering 8, no. 6 (June 29, 2018): 29. http://dx.doi.org/10.23956/ijarcsse.v8i6.714.

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Search Engine Optimization (SEO) is a technique which helps search engines to find and rank one site over another in response to a search query. SEO thus helps site owners to get traffic from search engines. Although the basic principle of operation of all search engines is the same, the minor differences between them lead to major changes in results relevancy. Choosing the right keywords to optimize for is thus the first and most crucial step to a successful SEO campaign. In the context of SEO, keyword density can be used as a factor in determining whether a webpage is relevant to a specified keyword or keyword phrase. SEO is known for its contribution as a process that affects the online visibility of a website or a webpage in a web search engine's results. In general, the earlier (or higher ranked on the search results page), and more frequently a website appears in the search results list, the more visitors it will receive from the search engine's users; these visitors can then be converted into customers. It is the objective of this paper to re-present black hat SEO technique as an unprofessional but profitable method of converting website users to customers. Having studied and understood white hat SEO, black hat SEO, gray hat SEO, crawling, indexing, processing and retrieving methods used by search engines as a web software program or web based script to search for documents and files for keywords over the internet to return the list of results containing those keywords; it would be seen that proper application of SEO gives website a better user experience, SEO helps build brand awareness through high rankings, SEO helps circumvent competition, and SEO gives room for high increased return on investment.
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Menemencioğlu, Oğuzhan, and İlhami Muharrem Orak. "A Review on Semantic Text and Multimedia Retrieval and Recent Trends." International Journal of Multimedia Data Engineering and Management 6, no. 1 (January 2015): 54–74. http://dx.doi.org/10.4018/ijmdem.2015010104.

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Semantic web works on producing machine readable data and aims to deal with large amount of data. The most important tool to access the data which exist in web is the search engine. Traditional search engines are insufficient in the face of the amount of data that consists in the existing web pages. Semantic search engines are extensions to traditional engines and overcome the difficulties faced by them. This paper summarizes semantic web, concept of traditional and semantic search engines and infrastructure. Also semantic search approaches are detailed. A summary of the literature is provided by touching on the trends. In this respect, type of applications and the areas worked for are considered. Based on the data for two different years, trend on these points are analyzed and impacts of changes are discussed. It shows that evaluation on the semantic web continues and new applications and areas are also emerging. Multimedia retrieval is a newly scope of semantic. Hence, multimedia retrieval approaches are discussed. Text and multimedia retrieval is analyzed within semantic search.
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Annalakshmi, Mu, and A. Padmapriya. "Structuring of Web Pages using XML Framework for Information Filtering." Asian Journal of Computer Science and Technology 8, S2 (March 5, 2019): 35–38. http://dx.doi.org/10.51983/ajcst-2019.8.s2.2028.

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Finding the required information in the vast area of web has been increasingly difficult in recent days since the web is overloaded with enormous content in the form of text, images, audio and video. Search engines help in this context to some extent but there are difficulties with them also. This paper proposes a framework in XML for the web pages in results of the search engines which helps in information filtering and search engine optimization.
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Strzelecki, Artur. "Eye-Tracking Studies of Web Search Engines: A Systematic Literature Review." Information 11, no. 6 (June 3, 2020): 300. http://dx.doi.org/10.3390/info11060300.

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This paper analyzes peer-reviewed empirical eye-tracking studies of behavior in web search engines. A framework is created to examine the effectiveness of eye-tracking by drawing on the results of, and discussions concerning previous experiments. Based on a review of 56 papers on eye-tracking for search engines from 2004 to 2019, a 12-element matrix for coding procedure is proposed. Content analysis shows that this matrix contains 12 common parts: search engine; apparatus; participants; interface; results; measures; scenario; tasks; language; presentation, research questions; and findings. The literature review covers results, the contexts of web searches, a description of participants in eye-tracking studies, and the types of studies performed on the search engines. The paper examines the state of current research on the topic and points out gaps in the existing literature. The review indicates that behavior on search engines has changed over the years. Search engines’ interfaces have been improved by adding many new functions and users have moved from desktop searches to mobile searches. The findings of this review provide avenues for further studies as well as for the design of search engines.
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Sharma, Prem Sagar, Divakar Yadav, and R. N. Thakur. "Web Page Ranking Using Web Mining Techniques: A Comprehensive Survey." Mobile Information Systems 2022 (May 31, 2022): 1–19. http://dx.doi.org/10.1155/2022/7519573.

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Due to the exponential growth of Internet users and traffic, information seekers depend highly on search engines to extract relevant information. Due to the accessibility of a large amount of textual, audio, video etc., contents, the responsibility of search engines has increased. The search engine provides relevant information to Internet users concerning their query, based on content, link structure, etc. However, it does not guarantee the correctness of the information. The performance of a search engine is highly dependent upon the ranking module. The performance of the ranking module is dependent upon the link structure of web pages, which analyze through Web structure mining (WSM) and their content, which analyzes through Web content mining (WCM). Web mining plays a vital role in computing the rank of web pages. This article presents web mining types, techniques, tools, algorithms, and their challenges. Further, it provides a critical comprehensive survey for the researchers by presenting different features of web pages, which are essential to check their quality. In this work, authors presented different approaches/techniques, algorithms and evaluation approaches in previous researches and identified some critical issues in page ranking and web mining, which provide future directions for the researchers working in the area.
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Lee, Sungin, Wonhong Jang, Eunsol Lee, and Sam G. Oh. "Search engine optimization." Library Hi Tech 34, no. 2 (June 20, 2016): 197–206. http://dx.doi.org/10.1108/lht-02-2016-0014.

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Purpose – The purpose of this paper is to examine the effect of, and identify core techniques of, search engine optimization (SEO) techniques applied to the web (http://lg-sl.net) and mobile (http//m.lg-sl.net) Science Land content and services at LG Sangnam Library in Korea. Design/methodology/approach – In accordance with three major SEO guidelines, ten SEO techniques were identified and applied, and their implications were extracted on three areas: improved search engine accessibility, increased relevance between site content and search engine keywords, and improved site credibility. The effects were quantitatively analyzed in terms of registered search engine keywords and influx of visits via search engines. Findings – This study shows that SEO techniques help increase the exposure of the library services and the number of visitors through search engines. Practical implications – SEO techniques have been applied to a few non-Korean information service organizations, but it is not a well-accepted practice in Korean libraries. And the dominant search engines in Korea have published their own SEO guidelines. Prior to this study, no significant endeavors have been undertaken in the context of Korean library services that have adopted SEO techniques to boost exposure of library services and increase user traffics. Originality/value – This is the first published study that has applied optimized SEO techniques to Korean web and mobile library services, in order to demonstrate the usefulness of the techniques for maximized exposure of library content.
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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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Iqbal, Muhammad, Muhammad Noman Khalid, Dr Amir Manzoor, Malik Munib Abid, and Nazir Ahmed Shaikh. "Search Engine Optimization (SEO): A Study of important key factors in achieving a better Search Engine Result Page (SERP) Position." Sukkur IBA Journal of Computing and Mathematical Sciences 6, no. 1 (July 21, 2022): 1–15. http://dx.doi.org/10.30537/sjcms.v6i1.924.

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Search Engines (SEs) have become the most significant tool for retrieving information from the World Wide Web (WWW) against user-generated queries. Presently, the data available on the Internet is growing exponentially in three different dimensions i.e. size, processing power, & software intelligence. The WWW has evolved from being a collection of static content (web 1.0) to intelligent web (Web 3.0). To reach a large audience on the internet, it is now essential for every business to have a website. However, to reach more viewers, a website must be visible on top of the Search Engine Result Page (SERP).This paper introduces the important concepts of Search Engine Optimization (SEO) and provides numerous guidelines for website developers to enhance the visibility of their websites in the eyes of search engines. The paper also discusses the role of link building for optimizing websites.
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Milonas, Elizabeth. "Does Design Contribute to Ease of Use: An Exploratory Study of Web Facets in The Result Pages of Two Search Engines." Advances in Classification Research Online 23, no. 1 (January 30, 2013): 62. http://dx.doi.org/10.7152/acro.v23i1.14606.

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An exploratory study was conduced to examine the design aspects of Web facets found in the search result pages of two search engines: Exalead and Excite. The goal of the study was to determine if Web facet design could contribute to perceived ease of use. This study builds upon findings from an earlier study (Milonas, 2010) in which the results indicated that users perceived the Web facets evident in the search result pages of the Exalead search engine easier to use than those found in Excite. The researcher surmised that the design of these Web facets might have contributed to the difference in perceived ease of use. The relationship between design and user perception in determining the ease of use of Web facets within these two search engines is explored. In the first component of the study, an expert inspection of the various design aspects of the search result pages of Exalead and Excite was conducted. In the second part of the study, five participants conducted an experiment using the Web facets found in the search result pages of the two search engines. Findings of both the expert inspection and the usability evaluation showed that there does not seem to be a significant difference in the design of Web facets within the two search engines. The findings seem to indicate that design of Web facets is not a contributory factor in terms of Web facet ease of use.
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Ma, Hong Yuan. "Design and Implementation of a Cache System in Web Search Engines." Applied Mechanics and Materials 462-463 (November 2013): 1106–9. http://dx.doi.org/10.4028/www.scientific.net/amm.462-463.1106.

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Web search engine caches the results which is frequently queried by users. It is an effective approach to improve the efficiency of Web search engines. In this paper, we give some valuable experience in our design and implementation of a Web search engine cache system. We present there design principles: logical layer processing, event-based communication architecture and avoiding frequent data copy. We also introduce the architecture presented in practice, including connection processor, application processor, query results caching processor, inverted list caching processor and list intersection caching processor. Experiments are conducted in our cache system using a real Web search engine query log.
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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 (November 30, 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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Al-Masri, Eyhab, and Qusay H. Mahmoud. "Discovering Web Services in Search Engines." IEEE Internet Computing 12, no. 3 (May 2008): 74–77. http://dx.doi.org/10.1109/mic.2008.53.

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Scales, B. Jane. "Authoritative guide to web search engines." Journal of Academic Librarianship 24, no. 3 (May 1998): 248. http://dx.doi.org/10.1016/s0099-1333(98)90051-9.

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Henzinger, Monika R. "Algorithmic Challenges in Web Search Engines." Internet Mathematics 1, no. 1 (January 2004): 115–23. http://dx.doi.org/10.1080/15427951.2004.10129079.

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BAXTER, BOB. "Traveling the Web with search engines." Nursing 27, no. 4 (April 1997): 30–31. http://dx.doi.org/10.1097/00152193-199704000-00017.

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Larkin, Marilynn. "What's amiss with web search engines?" Lancet 354, no. 9174 (July 1999): 260. http://dx.doi.org/10.1016/s0140-6736(05)66338-6.

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