Search (11 results, page 1 of 1)

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Abstract

The Web has become an information source for professional data gathering. Because of the vast amounts of information on almost all topics, one cannot systematically go over the whole set of results, and therefore must rely on the ordering of the results by the search engine. It is well known that search engines on the Web have low overlap in terms of coverage. In this study we measure how similar are the rankings of search engines on the overlapping results. We compare rankings of results for identical queries retrieved from several search engines. The method is based only on the set of URLs that appear in the answer sets of the engines being compared. For comparing the similarity of rankings of two search engines, the Spearman correlation coefficient is computed. When comparing more than two sets Kendall's W is used. These are well-known measures and the statistical significance of the results can be computed. The methods are demonstrated on a set of 15 queries that were submitted to four large Web search engines. The findings indicate that the large public search engines on the Web employ considerably different ranking algorithms.

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Abstract

In this study, we investigate the similarities and differences between rankings of search results by users and search engines. Sixty-seven students took part in a 3-week-long experiment, during which they were asked to identify and rank the top 10 documents from the set of URLs that were retrieved by three major search engines (Google, MSN Search, and Yahoo!) for 12 selected queries. The URLs and accompanying snippets were displayed in random order, without disclosing which search engine(s) retrieved any specific URL for the query. We computed the similarity of the rankings of the users and search engines using four nonparametric correlation measures in [0,1] that complement each other. The findings show that the similarities between the users' choices and the rankings of the search engines are low. We examined the effects of the presentation order of the results, and of the thinking styles of the participants. Presentation order influences the rankings, but overall the results indicate that there is no "average user," and even if the users have the same basic knowledge of a topic, they evaluate information in their own context, which is influenced by cognitive, affective, and physical factors. This is the first large-scale experiment in which users were asked to rank the results of identical queries. The analysis of the experimental results demonstrates the potential for personalized search.

Object

MSN Search

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Abstract

This study introduces methods for evaluating search engine performance over a time period. Several measures are defined, which as a whole describe search engine functionality over time. The necessary setup for such studies is described, and the use of these measures is illustrated through a specific example. The set of measures introduced here may serve as a guideline for the search engines for testing and improving their functionality. We recommend setting up a standard suite of measures for evaluating search engine performance.

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Abstract

Purpose - The objective of this paper is to characterize the changes in the rankings of the top ten results of major search engines over time and to compare the rankings between these engines. Design/methodology/approach - The papers compare rankings of the top-ten results of the search engines Google and AlltheWeb on ten identical queries over a period of three weeks. Only the top-ten results were considered, since users do not normally inspect more than the first results page returned by a search engine. The experiment was repeated twice, in October 2003 and in January 2004, in order to assess changes to the top-ten results of some of the queries during the three months interval. In order to assess the changes in the rankings, three measures were computed for each data collection point and each search engine. Findings - The findings in this paper show that the rankings of AlltheWeb were highly stable over each period, while the rankings of Google underwent constant yet minor changes, with occasional major ones. Changes over time can be explained by the dynamic nature of the web or by fluctuations in the search engines' indexes. The top-ten results of the two search engines had surprisingly low overlap. With such small overlap, the task of comparing the rankings of the two engines becomes extremely challenging. Originality/value - The paper shows that because of the abundance of information on the web, ranking search results is of extreme importance. The paper compares several measures for computing the similarity between rankings of search tools, and shows that none of the measures is fully satisfactory as a standalone measure. It also demonstrates the apparent differences in the ranking algorithms of two widely used search engines.

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Abstract

The World Wide Web was created in 1989, but it has already become a major information channel and source, influencing our everyday lives, commercial transactions, and scientific communication, to mention just a few areas. The seventeenth-century philosopher Descartes proclaimed, "I think, therefore I am" (cogito, ergo sum). Today the Web is such an integral part of our lives that we could rephrase Descartes' statement as "I have a Web presence, therefore I am." Because many people, companies, and organizations take this notion seriously, in addition to more substantial reasons for publishing information an the Web, the number of Web pages is in the billions and growing constantly. However, it is not sufficient to have a Web presence; tools that enable users to locate Web pages are needed as well. The major tools for discovering and locating information an the Web are search engines. This review discusses the use of Web search engines in information science research. Before going into detail, we should define the terms "information science," "Web search engine," and "use" in the context of this review.

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Abstract

We describe the results of an experiment designed to study user preferences for different orderings of search results from three major search engines. In the experiment, 65 users were asked to choose the best ordering from two different orderings of the same set of search results: Each pair consisted of the search engine's original top-10 ordering and a synthetic ordering created from the same top-10 results retrieved by the search engine. This process was repeated for 12 queries and nine different synthetic orderings. The results show that there is a slight overall preference for the search engines' original orderings, but the preference is rarely significant. Users' choice of the best result from each of the different orderings indicates that placement on the page (i.e., whether the result appears near the top) is the most important factor used in determining the quality of the result, not the actual content displayed in the top-10 snippets. In addition to the placement bias, we detected a small bias due to the reputation of the sites appearing in the search results.

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Abstract

Discusses the results of a case study in which 20 random queries were presented for ten consecutive days to Hotbot and Snap, two search tools that draw their results from the database of Inktomi. The results show huge daily fluctuations in the number of hits retrieved by Hotbot, and high stability in the hits displayed by Snap. These findings are to alert users of Hotbot of its instability as of October 1999, and they raise questions about the reliability of previous studies estimating the size of Hotbot based on its overlap with other search engines.

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Abstract

The World Wide Web has become one of our more important information sources, and commercial search engines are the major tools for locating information; however, it is not enough for a Web page to be indexed by the search engines-it also must rank high on relevant queries. One of the parameters involved in ranking is the number and quality of links pointing to the page, based on the assumption that links convey appreciation for a page. This article presents the results of a content analysis of the links to two top pages retrieved by Google for the query "jew" as of July 2004: the "jew" entry on the free online encyclopedia Wikipedia, and the home page of "Jew Watch," a highly anti-Semitic site. The top results for the query "jew" gained public attention in April 2004, when it was noticed that the "Jew Watch" homepage ranked number 1. From this point on, both sides engaged in "Googlebombing" (i.e., increasing the number of links pointing to these pages). The results of the study show that most of the links to these pages come from blogs and discussion links, and the number of links pointing to these pages in appreciation of their content is extremely small. These findings have implications for ranking algorithms based on link counts, and emphasize the huge difference between Web links and citations in the scientific community.

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Abstract

This article addresses the question of whether the Web can serve as an information source for research. Specifically, it analyzes by way of content analysis the Web pages retrieved by the major search engines on a particular date (June 7, 1998), as a result of the query 'informetrics OR informetric'. In 807 out of the 942 retrieved pages, the search terms were mentioned in the context of information science. Over 70% of the pages contained only indirect information on the topic, in the form of hypertext links and bibliographical references without annotation. The bibliographical references extracted from the Web pages were analyzed, and lists of most productive authors, most cited authors, works, and sources were compiled. The list of reference obtained from the Web was also compared to data retrieved from commercial databases. For most cases, the list of references extracted from the Web outperformed the commercial, bibliographic databases. The results of these comparisons indicate that valuable, freely available data is hidden in the Web waiting to be extracted from the millions of Web pages

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Abstract

The universe of information has been enriched by the creation of the World Wide Web, which has become an indispensible source for research. Since this source is growing at an enormous speed, an in-depth look of its performance to create a method for its evaluation has become necessary; however, growth is not the only process that influences the evolution of the Web. During their lifetime, Web pages may change their content and links to/from other Web pages, be duplicated or moved to a different URL, be removed from the Web either temporarily or permanently, and be temporarily inaccessible due to server and/or communication failures. To obtain a better understanding of these processes, we developed a method for tracking topics on the Web for long periods of time, without the need to employ a crawler and relying only on publicly available resources. The multiple data-collection methods used allow us to discover new pages related to the topic, to identify changes to existing pages, and to detect previously existing pages that have been removed or whose content is not relevant anymore to the specified topic. The method is demonstrated through monitoring Web pages that contain the term informetrics for a period of 8 years. The data-collection method also allowed us to analyze the dynamic changes in search engine coverage, illustrated here on Google - the search engine used for the longest period of time for data collection in this project.