Search (69 results, page 2 of 4)

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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

Citation analysis of documents retrieved from the Medline database (at the Web of Knowledge) has been possible only on a case-by-case basis. A technique is presented here for citation analysis in batch mode using both Medical Subject Headings (MeSH) at the Web of Knowledge and the Science Citation Index at the Web of Science (WoS). This freeware routine is applied to the case of "Brugada Syndrome," a specific disease and field of research (since 1992). The journals containing these publications, for example, are attributed to WoS categories other than "cardiac and cardiovascular systems", perhaps because of the possibility of genetic testing for this syndrome in the clinic. With this routine, all the instruments available for citation analysis can now be used on the basis of MeSH terms. Other options for crossing between Medline, WoS, and Scopus are also reviewed.

Object

Web of Knowledge

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Abstract

Domain visualization is one of the new research fronts resulted from the proliferation of information visualization, aiming to reveal the essence of a knowledge domain. Information visualization plays an integral role in modeling and representing intellectual structures associated with scientific disciplines. In this article, the domain of computer graphics is visualized based on author cocitation patterns derived from an 18-year span of the prestigious IEEE Computer Graphics and Applications (1982-1999). This domain visualization utilizes a series of visualization and animation techniques, including author cocitation maps, citation time lines, animation of a highdimensional specialty space, and institutional profiles. This approach not only augments traditional domain analysis and the understanding of scientific disciplines, but also produces a persistent and shared knowledge space for researchers to keep track the development of knowledge more effectively. The results of the domain visualization are discussed and triangulated in a broader context of the computer graphics field

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Abstract

Ahlgren, Jarneving, and. Rousseau review accepted procedures for author co-citation analysis first pointing out that since in the raw data matrix the row and column values are identical i,e, the co-citation count of two authors, there is no clear choice for diagonal values. They suggest the number of times an author has been co-cited with himself excluding self citation rather than the common treatment as zeros or as missing values. When the matrix is converted to a similarity matrix the normal procedure is to create a matrix of Pearson's r coefficients between data vectors. Ranking by r and by co-citation frequency and by intuition can easily yield three different orders. It would seem necessary that the adding of zeros to the matrix will not affect the value or the relative order of similarity measures but it is shown that this is not the case with Pearson's r. Using 913 bibliographic descriptions form the Web of Science of articles form JASIS and Scientometrics, authors names were extracted, edited and 12 information retrieval authors and 12 bibliometric authors each from the top 100 most cited were selected. Co-citation and r value (diagonal elements treated as missing) matrices were constructed, and then reconstructed in expanded form. Adding zeros can both change the r value and the ordering of the authors based upon that value. A chi-squared distance measure would not violate these requirements, nor would the cosine coefficient. It is also argued that co-citation data is ordinal data since there is no assurance of an absolute zero number of co-citations, and thus Pearson is not appropriate. The number of ties in co-citation data make the use of the Spearman rank order coefficient problematic.

Date

9. 7.2006 10:22:35

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Abstract

The increasing availability of digital libraries with cross-citation data on the Internet enables new studies in bibliometrics. The paper focuses on the list of 10.000 top-cited authors in computer science available as part of CiteSeer. Using data from several consecutive lists a model of how authors accrue citations with time is constructed. By comparing the rate at which individual authors accrue citations with the average rate, predictions are made of how their ranking in the list will change in the future.

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Abstract

Much has been written about the potential and pitfalls of macroscopic Web-based link analysis, yet there have been no studies that have provided clear statistical evidence that any of the proposed calculations can produce results over large areas of the Web that correlate with phenomena external to the Internet. This article attempts to provide such evidence through an evaluation of Ingwersen's (1998) proposed external Web Impact Factor (WIF) for the original use of the Web: the interlinking of academic research. In particular, it studies the case of the relationship between academic hyperlinks and research activity for universities in Britain, a country chosen for its variety of institutions and the existence of an official government rating exercise for research. After reviewing the numerous reasons why link counts may be unreliable, it demonstrates that four different WIFs do, in fact, correlate with the conventional academic research measures. The WIF delivering the greatest correlation with research rankings was the ratio of Web pages with links pointing at research-based pages to faculty numbers. The scarcity of links to electronic academic papers in the data set suggests that, in contrast to citation analysis, this WIF is measuring the reputations of universities and their scholars, rather than the quality of their publications

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Abstract

Discusses the Web of Science database recently introduced by ISI, and which is compiled from 8.000 journals covered in the SCI, SSCI and AHCI. Briefly compares the database with the Citation Indexes as provided by the BIDS service at the University of Bath. Explores the characteristics and usefulness of the WoS through a search of it for articles on the topic of image retrieval by shape matching. Suggests that the selection of articles of interest is much easier and far quicker using the WoS than other methods of conducting a search using ISI's data

Object

Web of Science

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Abstract

Chemical Abstracts Service recently unveiled citation searching in Chemical Abstracts. With Chemical Abstracts and Science Citation Index both now available for citation searching, this study compares the duplication and uniqueness of citing references for works of chemistry researchers for the years 1999-2001. The two indexes cover very similar source material, so one would expect the citation results to be very similar. This analysis of SciFinder Scholar and Web of Science shows some important differences as the databases are currently offered. Authors and institutions using citation counts as measures of scientific productivity should take note.

Object

Web of science

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Abstract

The use of citation counts to assess the impact of research articles is well established. However, the citation impact of an article can only be measured several years after it has been published. As research articles are increasingly accessed through the Web, the number of times an article is downloaded can be instantly recorded and counted. One would expect the number of times an article is read to be related both to the number of times it is cited and to how old the article is. The authors analyze how short-term Web usage impact predicts medium-term citation impact. The physics e-print archive-arXiv.org-is used to test this.

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Abstract

This article reveals different patterns of scholarly communication in the XML research field on the Web and in print journals in terms of author visibility, and challenges the common practice of exclusively using the ISI's databases to obtain citation counts as scientific performance indicators. Results from this study demonstrate both the importance and the feasibility of the use of multiple citation data sources in citation analysis studies of scholarly communication, and provide evidence for a developing "two tier" scholarly communication system.

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Abstract

A citation analysis of undergraduate term papers in microeconomics revealed a significant decrease in the frequency of scholarly resources cited between 1996 and 1999. Book citations decreased from 30% to 19%, newspaper citations increased from 7% to 19%, and Web citations increased from 9% to 21%. Web citations checked in 2000 revealed that only 18% of URLs cited in 1996 led to the correct Internet document. For 1999 bibliographies, only 55% of URLs led to the correct document. The authors recommend (1) setting stricter guidelines for acceptable citations in course assignments; (2) creating and maintaining scholarly portals for authoritative Web sites with a commitment to long-term access; and (3) continuing to instruct students how to critically evaluate resources

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Abstract

The Web of Science, an online database of bibliographic information produced by Thomson Reuters- draws its real value from the scholarly citation index at its core. By indexing the cited references from each paper as a separate part of the bibliographic data, a citation index creates a pathway by which a paper can be linked backward in time to the body of work that preceded it, as well as linked forward in time to its scholarly descendants. This entry provides a brief history of the development of the citation index, its core functionalities, and the way these unique data are provided to users through the Web of Science.

Object

Web of Science

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Abstract

The presence of clustering structure in the CF document collection (cystic fibrosis) is evaluated as a function of the exhaustivity of 5 composite representations. The composite representations are constructed from 2 subject descriptions, based on MeSH and subheadings, and 2 citation indexes, based on the complete set of references an and a comprehensive set of citations to each document. Experiment results reveal observable evidence of clustering structure diminishes as the exhaustivity of each representation is decreased. The representation composed of references and citations shows less evidence of clustering structure at the exhaustive level but more uniform evidence of clustering structure over a wide range of exhaustivity levels than composite representations that include subject descriptions. The structures imposed on the CF document collection by all composite representations satisfy the necessary condition for a meaningful clustering outcome

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Abstract

In two case studies of research units, reference values used to benchmark research performance appeared to show contradictory results: the average citation level in the subfields (FCSm) increased world-wide, while the citation level of the journals (JCSm) decreased, where concomitant changes were expected. Explanations were sought in: a shift in preference of document types; a change in publication preference for subfields; and changes in journal coverage. Publishing in newly covered journals with a low impact had a negative effect on impact ratios. However, the main factor behind the increase in FCSm was the distribution of articles across the five-year block periods that were studied. Publication in lower impact journals produced a lagging JCSm. Actual values of JCSm, FCSm, and citations per publication (CPP) values are not very informative either about research performance, or about the development of impact over time in a certain subfield with block indicators. Normalized citation impact indicators are free from such effects and should be consulted primarily in research performance assessments.

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Abstract

A variety of schemas and ontologies are currently used for the machine-readable description of bibliographic entities and citations. This diversity, and the reuse of the same ontology terms with different nuances, generates inconsistencies in data. Adoption of a single data model would facilitate data integration tasks regardless of the data supplier or context application. In this paper we present the OpenCitations Data Model (OCDM), a generic data model for describing bibliographic entities and citations, developed using Semantic Web technologies. We also evaluate the effective reusability of OCDM according to ontology evaluation practices, mention existing users of OCDM, and discuss the use and impact of OCDM in the wider open science community.

Content

Erschienen in: The Semantic Web - ISWC 2020, 19th International Semantic Web Conference, Athens, Greece, November 2-6, 2020, Proceedings, Part II. Vgl.: DOI: 10.1007/978-3-030-62466-8_28.

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Abstract

Reports recent experiences with the publishing, via the Internet and WWW of ISI's biweekly newspaper, The Scientist; which was originally mounted on the NSFnet. Compares the use of the Internet for SDI by comparing Web searches via AltaVista with similar searches on CD-ROM. Predicts that future current awareness services and SDI services will be linked to electronic periodicals in electronic libraries. Concludes with a note on cited reference searching, a variation on the theme of hypertext searching, with particular reference to SCI and Web crawlers

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Abstract

Main path analysis is a popular method for extracting the scientific backbone from the citation network of a research domain. Existing approaches ignored the semantic relationships between the citing and cited publications, resulting in several adverse issues, in terms of coherence of main paths and coverage of significant studies. This paper advocated the semantic main path network analysis approach to alleviate these issues based on citation function analysis. A wide variety of SciBERT-based deep learning models were designed for identifying citation functions. Semantic citation networks were built by either including important citations, for example, extension, motivation, usage and similarity, or excluding incidental citations like background and future work. Semantic main path network was built by merging the top-K main paths extracted from various time slices of semantic citation network. In addition, a three-way framework was proposed for the quantitative evaluation of main path analysis results. Both qualitative and quantitative analysis on three research areas of computational linguistics demonstrated that, compared to semantics-agnostic counterparts, different types of semantic main path networks provide complementary views of scientific knowledge flows. Combining them together, we obtained a more precise and comprehensive picture of domain evolution and uncover more coherent development pathways between scientific ideas.

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Abstract

Citation counts are widely used as indicators of research quality to support or replace human peer review and for lists of top cited papers, researchers, and institutions. Nevertheless, the relationship between citations and research quality is poorly evidenced. We report the first large-scale science-wide academic evaluation of the relationship between research quality and citations (field normalized citation counts), correlating them for 87,739 journal articles in 34 field-based UK Units of Assessment (UoA). The two correlate positively in all academic fields, from very weak (0.1) to strong (0.5), reflecting broadly linear relationships in all fields. We give the first evidence that the correlations are positive even across the arts and humanities. The patterns are similar for the field classification schemes of Scopus and Dimensions.ai, although varying for some individual subjects and therefore more uncertain for these. We also show for the first time that no field has a citation threshold beyond which all articles are excellent quality, so lists of top cited articles are not pure collections of excellence, and neither is any top citation percentile indicator. Thus, while appropriately field normalized citations associate positively with research quality in all fields, they never perfectly reflect it, even at high values.

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Date

13. 7.2008 19:53:22