Searching Web Documents Using a Fuzzy-Based Method

Authors

DOI:

https://doi.org/10.24203/ajfam.v5i2.4488

Keywords:

Web documents, Search algorithms, Type-2 fuzzy sets, Linguistic variables, User modeling

Abstract

Web searching could be more fruitful if a user could easily find documents which satisfy his/her needs in terms of structure, format and contents. Herein a solution through a fuzzy linguistic description of the document is proposed, a linguistic variant of standard metadata types. Linguistic expressions are used to qualitatively represent both meta-information and user needs and a matching system is developed to select the most compatible documents with the user profile. The documents retrieved by a web search engine are organized in clusters and ordered in each cluster.

Author Biographies

Enrico Fischetti, Dipartimento di Ingegneria Informatica (DIEM) University of Salerno Italy

Dipartimento di Ingegneria Informatica (DIEM)

Associate professor

Aniello Nappi, MANUCOR spa

Researcher

References

Demartini G.: “From People to Entities: New Semantic Search Paradigms for the Webâ€, in Studies on the Semantic Web, IOS Press, pp. 1-162, 2014

Ding W., Liu Y., Zhang J.: “Chinese-keyword Fuzzy Search and Extraction over Encrypted Patent Documentsâ€, Proc. Knowledge Discovery and Information Retrieval, pp.168-176, 2015

IEEE 1484.12.1-2002, Draft Standard for Learning Object Metadata, http://www.ieee.org, 2002.

IMS Learning Resource Metadata Information Model, Version 1.2.1 Final Specification, http://www.imsglobal.org/metadata, 2001.

Khattak A.M., Mustafa J., Ahmed N., Latif K., Khan S.: “Intelligent Search in Digital Documentsâ€, Web Intelligence, pp.558-561, 2008

Klusch M., Kapahnke P., Schulte S., Lécué F., Bernstein A.: “Semantic Web Service Search: A Brief Surveyâ€, Kunstliche Intelligenz 30(2), pp.139-147, 2016

Patro S., Malhotra V.M., Johnson D.: “An Algorithm to Use Feedback on Viewed Documents to Improve Web Query - Enabling Naïve Searchers to Search the Web Smartlyâ€, Proc. Web Information Systems and Technologies (1), pp.287-294, 2006

Qumsiyeh R., Ng Y. “Searching web documents using a summarization approachâ€, Int.J. Web Information Systems 12(1), pp.83-101, 2016

Saraçoglu R., Tütüncü K., Allahverdi N.: “A new approach on search for similar documents with multiple categories using fuzzy clusteringâ€, Expert Syst. Appl. 34(4), pp.2545-2554, 2008

Sartori E., Velegrakis Y.,Guerra F.: “Entity-Based Keyword Search in Web Documentsâ€, Trans. Computational Collective Intelligence 21, pp.21-49, 2016

Su F.,Xiao C.,, Gao C.,Gao Y.: “Adaptive method to support effective searching over large-scale web documentsâ€, Proc. Fuzzy Systems and Knowledge Discovery, pp.2428-2432, 2010

Ullah I., Khusro S.: “In Search of a Semantic Book Search Engine on the Web: Are We There Yet ?â€, Proc. Computer Science On-line Conference (1), pp.347-357, 2016

Yao Z., Wang B.: “Using section-semantic relation structures to enhance the performance of Web searchâ€, in Proc. Database and Expert Systems Applications, London, pp. 512-516, 2000

Weiland L., Scherp A.: “A Novel Approach for Semantics-Enabled Search of Multimedia Documents on the Webâ€, in Multimedia Modeling, pp.450-61, 2014

World Wide Web Consortium (W3C), Semantic Web, http://www.w3c.org, 2001.

Zadeh L. A., “The Concept of a Linguistic Variable and its Application to Approximate Reasoning- I, II, IIIâ€, Information Sciences I 8 – II 8 – III 9, pp. 199-249; pp.301-357; pp. 43-80, 1970

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Published

2017-04-22

How to Cite

Fischetti, E., & Nappi, A. (2017). Searching Web Documents Using a Fuzzy-Based Method. Asian Journal of Fuzzy and Applied Mathematics, 5(2). https://doi.org/10.24203/ajfam.v5i2.4488

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Section

Articles