-
Zhitomirsky-Geffet, M.; Bar-Ilan, J.: Towards maximal unification of semantically diverse ontologies for controversial domains (2014)
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- Abstract
- Purpose - Ontologies are prone to wide semantic variability due to subjective points of view of their composers. The purpose of this paper is to propose a new approach for maximal unification of diverse ontologies for controversial domains by their relations. Design/methodology/approach - Effective matching or unification of multiple ontologies for a specific domain is crucial for the success of many semantic web applications, such as semantic information retrieval and organization, document tagging, summarization and search. To this end, numerous automatic and semi-automatic techniques were proposed in the past decade that attempt to identify similar entities, mostly classes, in diverse ontologies for similar domains. Apparently, matching individual entities cannot result in full integration of ontologies' semantics without matching their inter-relations with all other-related classes (and instances). However, semantic matching of ontological relations still constitutes a major research challenge. Therefore, in this paper the authors propose a new paradigm for assessment of maximal possible matching and unification of ontological relations. To this end, several unification rules for ontological relations were devised based on ontological reference rules, and lexical and textual entailment. These rules were semi-automatically implemented to extend a given ontology with semantically matching relations from another ontology for a similar domain. Then, the ontologies were unified through these similar pairs of relations. The authors observe that these rules can be also facilitated to reveal the contradictory relations in different ontologies. Findings - To assess the feasibility of the approach two experiments were conducted with different sets of multiple personal ontologies on controversial domains constructed by trained subjects. The results for about 50 distinct ontology pairs demonstrate a good potential of the methodology for increasing inter-ontology agreement. Furthermore, the authors show that the presented methodology can lead to a complete unification of multiple semantically heterogeneous ontologies. Research limitations/implications - This is a conceptual study that presents a new approach for semantic unification of ontologies by a devised set of rules along with the initial experimental evidence of its feasibility and effectiveness. However, this methodology has to be fully automatically implemented and tested on a larger dataset in future research. Practical implications - This result has implication for semantic search, since a richer ontology, comprised of multiple aspects and viewpoints of the domain of knowledge, enhances discoverability and improves search results. Originality/value - To the best of the knowledge, this is the first study to examine and assess the maximal level of semantic relation-based ontology unification.
- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 66(2014) no.5, S.494-518
-
Bar-Ilan, J.: ¬The Web as an information source on informetrics? : A content analysis (2000)
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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
- Source
- Journal of the American Society for Information Science. 51(2000) no.5, S.432-443
-
Bar-Ilan, J.: What do we know about links and linking? : a framework for studying links in academic environments (2005)
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- Abstract
- The Web is an enormous set of documents connected through hypertext links created by authors of Web pages. These links have been studied quantitatively, but little has been done so far in order to understand why these links are created. As a first step towards a better understanding, we propose a classification of link types in academic environments on the Web. The classification is multi-faceted and involves different aspects of the source and the target page, the link area and the relationship between the source and the target. Such classification provides an insight into the diverse uses of hypertext links on the Web, and has implications for browsing and ranking in IR systems by differentiating between different types of links. As a case study we classified a sample of links between sites of Israeli academic institutions.
- Source
- Information processing and management. 41(2005) no.4, S.973-986
-
Bronstein, J.; Gazit, T.; Perez, O.; Bar-Ilan, J.; Aharony, N.; Amichai-Hamburger, Y.: ¬An examination of the factors contributing to participation in online social platforms (2016)
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- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 68(2016) no.6, S.793-818
-
Zhitomirsky-Geffet, M.; Bar-Ilan, J.; Levene, M.: Testing the stability of "wisdom of crowds" judgments of search results over time and their similarity with the search engine rankings (2016)
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- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 68(2016) no.4, S.407-427
-
Bar-Ilan, J.: Information hub blogs (2005)
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- Source
- Journal of information science. 31(2005) no.4, S.297-307
-
Bar-Ilan, J.; Gutman,T.: How do search engines respond to some non-English queries? (2005)
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- Source
- Journal of information science. 31(2005) no.1, S.13-
-
Lazinger, S.S.; Peritz, B.C.; Bar-Ilan, J.: Using a local area network as an interface to wide area networks in library and information science education (1993)
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- Pages
- S.651-660
-
Bar-Ilan, J.; Levene, M.: ¬The hw-rank : an h-index variant for ranking web pages (2015)
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- Source
- Scientometrics. 102(2015) no.3, S.2247-2253
-
Bar-Ilan, J.: Methods for measuring search engine performance over time (2002)
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- Source
- Journal of the American Society for Information Science and technology. 53(2002) no.4, S.308-319
-
Bar-Ilan, J.; Keenoy, K.; Yaari, E.; Levene, M.: User rankings of search engine results (2007)
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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.
- Source
- Journal of the American Society for Information Science and Technology. 58(2007) no.9, S.1254-1266
-
Bar-Ilan, J.; Zhitomirsky-Geffet, M.; Miller, Y.; Shoham, S.: ¬The effects of background information and social interaction on image tagging (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.5, S.940-951
-
Shema, H.; Bar-Ilan, J.; Thelwall, M.: How is research blogged? : A content analysis approach (2015)
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- Abstract
- Blogs that cite academic articles have emerged as a potential source of alternative impact metrics for the visibility of the blogged articles. Nevertheless, to evaluate more fully the value of blog citations, it is necessary to investigate whether research blogs focus on particular types of articles or give new perspectives on scientific discourse. Therefore, we studied the characteristics of peer-reviewed references in blogs and the typical content of blog posts to gain insight into bloggers' motivations. The sample consisted of 391 blog posts from 2010 to 2012 in Researchblogging.org's health category. The bloggers mostly cited recent research articles or reviews from top multidisciplinary and general medical journals. Using content analysis methods, we created a general classification scheme for blog post content with 10 major topic categories, each with several subcategories. The results suggest that health research bloggers rarely self-cite and that the vast majority of their blog posts (90%) include a general discussion of the issue covered in the article, with more than one quarter providing health-related advice based on the article(s) covered. These factors suggest a genuine attempt to engage with a wider, nonacademic audience. Nevertheless, almost 30% of the posts included some criticism of the issues being discussed.
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.6, S.1136-1149
-
Lazinger, S.S.; Bar-Ilan, J.; Peritz, B.C.: Internet use by faculty members in various disciplines : a comparative case study (1997)
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- Source
- Journal of the American Society for Information Science. 48(1997) no.6, S.508-518
-
Bar-Ilan, J.: Evaluating the stability of the search tools Hotbot and Snap : a case study (2000)
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- Source
- Online information review. 24(2000) no.6, S.439-449
-
Bar-Ilan, J.: On the overlap, the precision and estimated recall of search engines : a case study of the query 'Erdös' (1998)
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- Source
- Scientometrics. 42(1998) no.2, S.207-228
-
Bar-Ilan, J.; Peritz, B.C.: Evolution, continuity, and disappearance of documents on a specific topic an the Web : a longitudinal study of "informetrics" (2004)
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Bar-Ilan, J.; Peritz, B.C.: Informetric theories and methods for exploring the Internet : an analytical survey of recent research literature (2002)
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