Fuzzy ontologies for information retrieval on the WWW

Abstract Fuzzy logic and soft computing have important roles to play in the development of the semantic web. Ontologies represent a means of representing and sharing knowledge between users and systems, and are important tool for information retrieval. However many different ontologies have been established, and communication between them can be difficult. In particular, many terms are located in multiple locations within large ontologies. Different stakeholders in the information retrieval process, “Authors”, “Readers” and “Librarians”, are identified. This work deals with the concept of the “Fuzzy Ontology”, which is designed to allow the representation of differing viewpoints within a single framework. The means of constructing, refinement and use of the fuzzy ontology are described. Fuzzy ontology membership values can be learned from documents or users, based around existing ontologies such as the Unified Medical Language System (UMLS). Use of the fuzzy ontology approach for information retrieval may allow the efficient sharing of knowledge between users and groups.

[1]  Janusz Kacprzyk,et al.  Intelligent Exploration of the Web , 2003, Studies in Fuzziness and Soft Computing.

[2]  David Parry,et al.  Fuzzification of a standard ontology to encourage reuse , 2004, Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, 2004. IRI 2004..

[3]  Peter J. Nürnberg,et al.  Proceedings of the Fifth ACM Conference on Digital Libraries, June 2-7, 2000, San Antonio, TX, USA , 2000 .

[4]  Frank M. Shipman,et al.  Proceedings of the eleventh ACM on Hypertext and hypermedia , 2000 .

[5]  Dennis Wollersheim,et al.  Methodology for creating a sample subset of dynamic taxonomy to use in navigating medical text databases , 2002, Proceedings International Database Engineering and Applications Symposium.

[6]  Lucas M. Bachmann,et al.  Research Paper: Identifying Diagnostic Studies in MEDLINE: Reducing the Number Needed to Read , 2002, J. Am. Medical Informatics Assoc..

[7]  Amanda Spink,et al.  Vox populi: The public searching of the web , 2001, J. Assoc. Inf. Sci. Technol..

[8]  D. Sackett.  Evidence-Based Medicine: How to Practice and Teach EBM , 2018 .

[9]  Mark A. Musen.  Creating and Using Ontologies: What Informatics is All About , 2001, MedInfo.

[10]  Charles L. Viles,et al.  User effort in query construction and interface selection , 2000, DL '00.

[11]  Christine L. Borgman,et al.  Why are Online Catalogs Hard to Use? Lessons Learned from Information=Retrieval Studies , 1986 .

[12]  R Brian Haynes,et al.  BMC Medicine BioMed Central , 2003 .

[13]  D. R. Swanson.  Historical note: information retrieval and the future of an illusion , 1997 .

[14]  Slawomir Zadrozny,et al.  FQUERY for Access: towards human consistent querying user interface , 1996, SAC '96.

[15]  David Parry,et al.  A fuzzy ontology for medical document retrieval , 2004, ACSW.

[16]  Udo Kruschwitz.  An Adaptable Search System for Collections of Partially Structured Documents , 2003, IEEE Intell. Syst..

[17]  Fabio Crestani,et al.  “Is this document relevant?…probably”: a survey of probabilistic models in information retrieval , 1998, CSUR.

[18]  Mark A. Musen,et al.  SMART: Automated Support for Ontology Merging and Alignment , 1999 .

[19]  John Yen,et al.  Using fuzzy ontology for query refinement in a personalized abstract search engine , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[20]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[21]  K. M. George,et al.  Proceedings of the 1996 ACM Symposium on Applied Computing, SAC'96, Philadelphia, PA, USA, February 17-19, 1996 , 1996, SAC.

[22]  Jaap Gordijn,et al.  Value Webs: using ontologies to bundle real-world services , 2004, IEEE Intelligent Systems.

[23]  Toru Yamaguchi,et al.  Data retrieval using conceptual fuzzy sets , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).

[24]  R. Haynes,et al.  Medline : analytical survey scientifically strong studies of diagnosis from Optimal search strategies for retrieving , 2004 .

[25]  D G Altman,et al.  Calculating the number needed to treat for trials where the outcome is time to an event , 1999, BMJ.

[26]  Roy Rada,et al.  An object-oriented approach to knowledge representation in a biomedical domain , 1994, Artif. Intell. Medicine.

[27]  Sylvie Ranwez,et al.  Ontology-supported and ontology-driven conceptual navigation on the World Wide Web , 2000, HYPERTEXT '00.

[28]  Bernard J. Jansen,et al.  Coverage, relevance, and ranking: The impact of query operators on Web search engine results , 2003, TOIS.

[29]  Michael E. Lesk,et al.  Computer Evaluation of Indexing and Text Processing , 1968, JACM.

[30]  Christine L. Borgman,et al.  Why are online catalogsstill hard to use , 1996 .

[31]  Nicola Guarino,et al.  Semantic Matching: Formal Ontological Distinctions for Information Organization, Extraction, and Integration , 1997, SCIE.

[32]  Janusz Kacprzyk,et al.  Database Queries with Fuzzy Linguistic Quantifiers , 1986, IEEE Transactions on Systems, Man, and Cybernetics.

[33]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[34]  Carlo Strapparava,et al.  Proceedings of the Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems , 2000 .

[35]  Christine L. Borgman,et al.  Why are online catalogs still hard to use , 1996 .

[36]  Maria Teresa Pazienza,et al.  Information Extraction A Multidisciplinary Approach to an Emerging Information Technology , 1997, Lecture Notes in Computer Science.

[37]  Stuart E. Middleton,et al.  Ontological user profiling in recommender systems , 2004, TOIS.

[38]  Rada Mihalcea,et al.  Word semantics for information retrieval: moving one step closer to the Semantic Web , 2001, Proceedings 13th IEEE International Conference on Tools with Artificial Intelligence. ICTAI 2001.

[39]  Sarah K. Brem,et al.  Using Critical Thinking To Conduct Effective Searches of Online Resources. ERIC Digest. , 2000 .

[40]  Patrick Bosc,et al.  Fuzzy querying with SQL: extensions and implementation aspects , 1988 .

[41]  Fabio Crestani,et al.  Soft computing in information retrieval: techniques and applications , 2000 .

[42]  Steffen Staab,et al.  Knowledge Portals: Ontologies at Work , 2001, AI Mag..

[43]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[44]  S W Tu,et al.  PROTEGE-II: computer support for development of intelligent systems from libraries of components. , 1995, Medinfo. MEDINFO.

[45]  Stefan Decker,et al.  Creating Semantic Web Contents with Protégé-2000 , 2001, IEEE Intell. Syst..

[46]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[47]  Yuri Kagolovsky,et al.  A New Approach to the Concept of "Relevance" in Information Retrieval (IR) , 2001, MedInfo.

[48]  Slawomir Zadrozny,et al.  Internet as a Challenge to Fuzzy Querying , 2003, Intelligent Exploration of the Web.

[49]  G. Pasi,et al.  Application of Fuzzy Set Theory to Extend Boolean Information Retrieval , 2000 .

[50]  Michael D. Gordon,et al.  Web Search---Your Way , 2001, CACM.

[51]  Olivier Bodenreider,et al.  Circular hierarchical relationships in the UMLS: etiology, diagnosis, treatment, complications and prevention , 2001, AMIA.

[52]  William P. Birmingham,et al.  Architecture of a metasearch engine that supports user information needs , 1999, CIKM '99.

[53]  Lawrence M. Rudner,et al.  Quality of Researchers' Searches of the ERIC Database , 1999 .

[54]  Bin Ma,et al.  The similarity metric , 2001, IEEE Transactions on Information Theory.

[55]  Amanda Spink,et al.  From E-Sex to E-Commerce: Web Search Changes , 2002, Computer.

[56]  C. J. van Rijsbergen,et al.  The use of hierarchic clustering in information retrieval , 1971, Inf. Storage Retr..

[57]  C. J. van Rijsbergen,et al.  Finding Out About: A Cognitive Perspective on Search Engine Technology and the WWW , 2001 .

[58]  N. F. Noy,et al.  Ontology Development 101: A Guide to Creating Your First Ontology , 2001 .