Search (195 results, page 1 of 10)

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Abstract

Investigates the retrieval capabilities of 6 Internet search engines on a simple query. Existing work on search engine evaluation considers only the first 10 or 20 results returned by the search engine. In this work, all documents that the search engine pointed at were retrieved and thoroughly examined. Thus the precision of the whole retrieval process could be calculated, the overlap between the results of the engines studied, and an estimate on the recall of the searches given. The precision of the engines is high, recall is very low and the overlap is minimal

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Abstract

Search engines index only a proportion of the web and this proportion is not determined randomly but by following algorithms that take into account the properties that impact factors measure. A survey was conducted in order to test the coverage of search engines and to decide thether their partial coverage is indeed an obstacle to using them to calculate web impact factors. The results indicate that search engine coverage, even of large national domains is extremely uneven and would be likely to lead to misleading calculations

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Abstract

Search engines are normally used to find information or Web sites, but Webometric investigations use them for quantitative data such as the number of pages matching a query and the international spread of those pages. For this type of application, the accuracy of the hit count estimates and range of URLs in the full results are important. Here, we compare the applications programming interfaces of Google, Yahoo!, and Live Search for 1,587 single word searches. The hit count estimates were broadly consistent but with Yahoo! and Google, reporting 5-6 times more hits than Live Search. Yahoo! tended to return slightly more matching URLs than Google, with Live Search returning significantly fewer. Yahoo!'s result URLs included a significantly wider range of domains and sites than the other two, and there was little consistency between the three engines in the number of different domains. In contrast, the three engines were reasonably consistent in the number of different top-level domains represented in the result URLs, although Yahoo! tended to return the most. In conclusion, quantitative results from the three search engines are mostly consistent but with unexpected types of inconsistency that users should be aware of. Google is recommended for hit count estimates but Yahoo! is recommended for all other Webometric purposes.

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Abstract

The rapid development of Web sites providing extensive coverage of a topic, coupled with the development of powerful search engines (designed to help users find such Web sites), suggests that users can easily find comprehensive information about a topic. In domains such as consumer healthcare, finding comprehensive information about a topic is critical as it can improve a patient's judgment in making healthcare decisions, and can encourage higher compliance with treatment. However, recent studies show that despite using powerful search engines, many healthcare information seekers have difficulty finding comprehensive information even for narrow healthcare topics because the relevant information is scattered across many Web sites. To date, no studies have analyzed how facts related to a search topic are distributed across relevant Web pages and Web sites. In this study, the distribution of facts related to five common healthcare topics across high-quality sites is analyzed, and the reasons underlying those distributions are explored. The analysis revealed the existence of few pages that had many facts, many pages that had few facts, and no single page or site that provided all the facts. While such a distribution conforms to other information-related phenomena, a deeper analysis revealed that the distributions were caused by a trade-off between depth and breadth, leading to the existence of general, specialized, and sparse pages. Furthermore, the results helped to make explicit the knowledge needed by searchers to find comprehensive healthcare information, and suggested the motivation to explore distribution-conscious approaches for the development of future search systems, search interfaces, Web page designs, and training.

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Abstract

Continued development of the Internet requires the development of efficient, easy-to-use search engines. Ideally, such development should call upon knowledge and skills from a variety of disciplines, including computer science, information science, psychology, and ergonomics. The current study is intended to determine whether search engines shows a pattern of interdisciplinarity. 2 disciplines were selected as the focus for the study: computer science, and library/information science. A citation analysis was conducted to measure levels of interdisciplinary research and publishing in Internet search engine design and development. The results show a higher level of interdisciplinarity among library and information scientists than among computer scientists or among any of those categorized as 'other'. This is reflected both in the types of journals in which the authors publish, and in the references they cite to support their work. However, almost no authors published articles or cited references in fields such as cognitive science, ergonomics, or psychology. The results of this study are analyzed in terms of the writings of Patrick Wilson, Bruno Latour, Pierre Bordieu, Fritz Ringer, and Thomas Pinelli, focusing on cognitive authority within a profession, interaction between disciplines, and information-gathering habits of professionals. Suggestions for further research are given

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Abstract

Because of the increasing presence of scientific publications an the Web, combined with the existing difficulties in easily verifying and retrieving these publications, research an techniques and methods for retrieval of scientific Web publications is called for. In this article, we report an the initial steps taken toward the construction of a test collection of scientific Web publications within the subject domain of plant biology. The steps reported are those of data gathering and data analysis aiming at identifying characteristics of scientific Web publications. The data used in this article were generated based an specifically selected domain topics that are searched for in three publicly accessible search engines (Google, AlITheWeb, and AItaVista). A sample of the retrieved hits was analyzed with regard to how various publication attributes correlated with the scientific quality of the content and whether this information could be employed to harvest, filter, and rank Web publications. The attributes analyzed were inlinks, outlinks, bibliographic references, file format, language, search engine overlap, structural position (according to site structure), and the occurrence of various types of metadata. As could be expected, the ranked output differs between the three search engines. Apparently, this is caused by differences in ranking algorithms rather than the databases themselves. In fact, because scientific Web content in this subject domain receives few inlinks, both AItaVista and AlITheWeb retrieved a higher degree of accessible scientific content than Google. Because of the search engine cutoffs of accessible URLs, the feasibility of using search engine output for Web content analysis is also discussed.

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Abstract

This article offers a comparative analysis of the personal profiling capabilities of the two most important free citation-based academic search engines, namely, Microsoft Academic Search (MAS) and Google Scholar Citations (GSC). Author profiles can be useful for evaluation purposes once the advantages and the shortcomings of these services are described and taken into consideration. In total, 771 personal profiles appearing in both the MAS and the GSC databases were analyzed. Results show that the GSC profiles include more documents and citations than those in MAS but with a strong bias toward the information and computing sciences, whereas the MAS profiles are disciplinarily better balanced. MAS shows technical problems such as a higher number of duplicated profiles and a lower updating rate than GSC. It is concluded that both services could be used for evaluation proposes only if they are applied along with other citation indices as a way to supplement that information.

Object

Microsoft academic search

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Abstract

Web impact factors, the proposed web equivalent of impact factors for journals, can be calculated by using search engines. It has been found that the results are problematic because of the variable coverage of search engines as well as their ability to give significantly different results over short periods of time. The fundamental problem is that although some search engines provide a functionality that is capable of being used for impact calculations, this is not their primary task and therefore they do not give guarantees as to performance in this respect. In this paper, a bespoke web crawler designed specifically for the calculation of reliable WIFs is presented. This crawler was used to calculate WIFs for a number of UK universities, and the results of these calculations are discussed. The principal findings were that with certain restrictions, WIFs can be calculated reliably, but do not correlate with accepted research rankings owing to the variety of material hosted on university servers. Changes to the calculations to improve the fit of the results to research rankings are proposed, but there are still inherent problems undermining the reliability of the calculation. These problems still apply if the WIF scores are taken on their own as indicators of the general impact of any area of the Internet, but with care would not apply to online journals.

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Abstract

We present PubSearch, a hybrid heuristic scheme for re-ranking academic papers retrieved from standard digital libraries such as the ACM Portal. The scheme is based on the hierarchical combination of a custom implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper's index terms with each other. We designed and developed a meta-search engine that submits user queries to standard digital repositories of academic publications and re-ranks the repository results using the hierarchical heuristic scheme. We evaluate our proposed re-ranking scheme via user feedback against the results of ACM Portal on a total of 58 different user queries specified from 15 different users. The results show that our proposed scheme significantly outperforms ACM Portal in terms of retrieval precision as measured by most common metrics in Information Retrieval including Normalized Discounted Cumulative Gain (NDCG), Expected Reciprocal Rank (ERR) as well as a newly introduced lexicographic rule (LEX) of ranking search results. In particular, PubSearch outperforms ACM Portal by more than 77% in terms of ERR, by more than 11% in terms of NDCG, and by more than 907.5% in terms of LEX. We also re-rank the top-10 results of a subset of the original 58 user queries produced by Google Scholar, Microsoft Academic Search, and ArnetMiner; the results show that PubSearch compares very well against these search engines as well. The proposed scheme can be easily plugged in any existing search engine for retrieval of academic publications.

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Abstract

The primary webometric method for estimating the online impact of an organization is to count links to its website. Link counts have been available from commercial search engines for over a decade but this was set to end by early 2012 and so a replacement is needed. This article compares link counts to two alternative methods: URL citations and organization title mentions. New variations of these methods are also introduced. The three methods are compared against each other using Yahoo!. Two of the three methods (URL citations and organization title mentions) are also compared against each other using Bing. Evidence from a case study of 131 UK universities and 49 US Library and Information Science (LIS) departments suggests that Bing's Hit Count Estimates (HCEs) for popular title searches are not useful for webometric research but that Yahoo!'s HCEs for all three types of search and Bing's URL citation HCEs seem to be consistent. For exact URL counts the results of all three methods in Yahoo! and both methods in Bing are also consistent. Four types of accuracy factors are also introduced and defined: search engine coverage, search engine retrieval variation, search engine retrieval anomalies, and query polysemy.

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Abstract

Purpose - Link analysis is an established topic within webometrics. It normally uses counts of links between sets of web sites or to sets of web sites. These link counts are derived from web crawlers or commercial search engines with the latter being the only alternative for some investigations. This paper compares link counts with URL citation counts in order to assess whether the latter could be a replacement for the former if the major search engines withdraw their advanced hyperlink search facilities. Design/methodology/approach - URL citation counts are compared with link counts for a variety of data sets used in previous webometric studies. Findings - The results show a high degree of correlation between the two but with URL citations being much less numerous, at least outside academia and business. Research limitations/implications - The results cover a small selection of 15 case studies and so the findings are only indicative. Significant differences between results indicate that the difference between link counts and URL citation counts will vary between webometric studies. Practical implications - Should link searches be withdrawn, then link analyses of less well linked non-academic, non-commercial sites would be seriously weakened, although citations based on e-mail addresses could help to make citations more numerous than links for some business and academic contexts. Originality/value - This is the first systematic study of the difference between link counts and URL citation counts in a variety of contexts and it shows that there are significant differences between the two.

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Content

The volume of scientific literature typically far exceeds the ability of scientists to identify and utilize all relevant information in their research. Improvements to the accessibility of scientific literature, allowing scientists to locate more relevant research within a given time, have the potential to dramatically improve communication and progress in science. With the web, scientists now have very convenient access to an increasing amount of literature that previously required trips to the library, inter-library loan delays, or substantial effort in locating the source. Evidence shows that usage increases when access is more convenient, and maximizing the usage of the scientific record benefits all of society. Although availability varies greatly by discipline, over a million research articles are freely available on the web. Some journals and conferences provide free access online, others allow authors to post articles on the web, and others allow authors to purchase the right to post their articles on the web. In this article we investigate the impact of free online availability by analyzing citation rates. We do not discuss methods of creating free online availability, such as time-delayed release or publication/membership/conference charges. Online availability of an article may not be expected to greatly improve access and impact by itself. For example, efficient means of locating articles via web search engines or specialized search services is required, and a substantial percentage of the literature needs to be indexed by these search services before it is worthwhile for many scientists to use them. Computer science is a forerunner in web availability -- a substantial percentage of the literature is online and available through search engines such as Google (google.com), or specialized services such as ResearchIndex (researchindex.org). Even so, the greatest impact of the online availability of computer science literature is likely yet to come, because comprehensive search services and more powerful search methods have only become available recently. We analyzed 119,924 conference articles in computer science and related disciplines, obtained from DBLP (dblp.uni-trier.de). In computer science, conference articles are typically formal publications and are often more prestigious than journal articles, with acceptance rates at some conferences below 10%. Citation counts and online availability were estimated using ResearchIndex. The analysis excludes self-citations, where a citation is considered to be a self-citation if one or more of the citing and cited authors match.

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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

Although time has been recognized as an important dimension in the co-citation literature, to date it has not been incorporated into the analogous process of link analysis an the Web. In this paper, we discuss several aspects and uses of the time dimension in the context of Web information retrieval. We describe the ideal casewhere search engines track and store temporal data for each of the pages in their repository, assigning timestamps to the hyperlinks embedded within the pages. We introduce several applications which benefit from the availability of such timestamps. To demonstrate our claims, we use a somewhat simplistic approach, which dates links by approximating the age of the page's content. We show that by using this crude measure alone it is possible to detect and expose significant events and trends. We predict that by using more robust methods for tracking modifications in the content of pages, search engines will be able to provide results that are more timely and better reflect current real-life trends than those they provide today.

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Abstract

In this article, I investigate the reliability, in the social science sense, of collecting informetric data about the World Wide Web by Web crawling. The investigation includes a critical examination of the practice of Web crawling and contrasts the results of content crawling with the results of link crawling. It is shown that Web crawling by search engines is intentionally biased and selective. I also report the results of a [arge-scale experimental simulation of Web crawling that illustrates the effects of different crawling policies an data collection. It is concluded that the reliability of Web crawling as a data collection technique is improved by fuller reporting of relevant crawling policies.

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Content

"Zur Kurzmitteilung "Latest enhancements in Scopus: ... h-Index incorporated in Scopus" in den letzten Online-Mitteilungen (Online-Mitteilungen 92, S.31) ist zu korrigieren, dass der h-Index sehr wohl bereits im Web of Science enthalten ist. Allerdings findet man/frau diese Information nicht in der "cited ref search", sondern neben der Trefferliste einer Quick Search, General Search oder einer Suche über den Author Finder in der rechten Navigationsleiste unter dem Titel "Citation Report". Der "Citation Report" bietet für die in der jeweiligen Trefferliste angezeigten Arbeiten: - Die Gesamtzahl der Zitierungen aller Arbeiten in der Trefferliste - Die mittlere Zitationshäufigkeit dieser Arbeiten - Die Anzahl der Zitierungen der einzelnen Arbeiten, aufgeschlüsselt nach Publikationsjahr der zitierenden Arbeiten - Die mittlere Zitationshäufigkeit dieser Arbeiten pro Jahr - Den h-Index (ein h-Index von x sagt aus, dass x Arbeiten der Trefferliste mehr als x-mal zitiert wurden; er ist gegenüber sehr hohen Zitierungen einzelner Arbeiten unempfindlicher als die mittlere Zitationshäufigkeit)."

Date

6. 4.2008 19:04:22

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Abstract

In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing.

Date

22. 3.2009 17:49:11

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Abstract

The Web is a huge source of information, and one of the main problems facing users is finding documents which correspond to their requirements. Apart from the problem of thematic relevance, the documents retrieved by search engines do not always meet the users' expectations. The document may be too general, or conversely too specialized, or of a different type from what the user is looking for, and so forth. We think that adding metadata to pages can considerably improve the process of searching for information an the Web. This article presents a possible typology for Web sites and pages, as weIl as a method for propagating metadata values, based an the study of the Web graph and more specifically the method of cocitation in this graph.

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Abstract

To test feasibility of cybermetric indicators for describing and ranking university activities as shown in their Web sites, a large set of 9,330 institutions worldwide was compiled and analyzed. Using search engines' advanced features, size (number of pages), visibility (number of external inlinks), and number of rich files (pdf, ps, doc, ppt, and As formats) were obtained for each of the institutional domains of the universities. We found a statistically significant correlation between a Web ranking built on a combination of Webometric data and other university rankings based on bibliometric and other indicators. Results show that cybermetric measures could be useful for reflecting the contribution of technologically oriented institutions, increasing the visibility of developing countries, and improving the rankings based on Science Citation Index (SCI) data with known biases.

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Abstract

Webometrics is an information science field concerned with measuring aspects of the World Wide Web (WWW) for a variety of information science research goals. It came into existence about five years after the Web was formed and has since grown to become a significant aspect of information science, at least in terms of published research. Although some webometrics research has focused on the structure or evolution of the Web itself or the performance of commercial search engines, most has used data from the Web to shed light on information provision or online communication in various contexts. Most prominently, techniques have been developed to track, map, and assess Web-based informal scholarly communication, for example, in terms of the hyperlinks between academic Web sites or the online impact of digital repositories. In addition, a range of nonacademic issues and groups of Web users have also been analyzed.