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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
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Bar-Ilan, J.: Information hub blogs (2005)
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Bar-Ilan, J.; Gutman,T.: How do search engines respond to some non-English queries? (2005)
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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
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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
-
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.
-
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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-
Bar-Ilan, J.; Levene, M.: ¬The hw-rank : an h-index variant for ranking web pages (2015)
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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
-
Bar-Ilan, J.: Methods for measuring search engine performance over time (2002)
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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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Bar-Ilan, J.: Evaluating the stability of the search tools Hotbot and Snap : a case study (2000)
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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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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.: ¬The use of Web search engines in information science research (2003)
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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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Bar-Ilan, J.: Informetrics (2009)
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Shema, H.; Bar-Ilan, J.; Thelwall, M.: Do blog citations correlate with a higher number of future citations? : Research blogs as a potential source for alternative metrics (2014)
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