Web intelligence: A fuzzy knowledge-based framework for the enhancement of querying and accessing web data

Jaafar, J. and Danyaro, K.U. and Liew, M.S. (2015) Web intelligence: A fuzzy knowledge-based framework for the enhancement of querying and accessing web data. IGI Global, pp. 83-104.

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Abstract

This chapter discusses about the veracity of data. The veracity issue is the challenge of imprecision in big data due to influx of data from diverse sources. To overcome this problem, this chapter proposes a fuzzy knowledge-based framework that will enhance the accessibility of Web data and solve the inconsistency in data model. D2RQ, protégé, and fuzzy Web Ontology Language applications were used for configuration and performance. The chapter also provides the completeness fuzzy knowledge-based algorithm, which was used to determine the robustness and adaptability of the knowledge base. The result shows that the D2RQ is more scalable with respect to performance comparison. Finally, the conclusion and future lines of the research were provided. © 2015, IGI Global. All rights reserved.

Item Type: Book
Impact Factor: cited By 2
Uncontrolled Keywords: Knowledge based systems; Ontology, Fuzzy knowledge; Knowledge base; Performance comparison; Web data; Web intelligence; Web ontology language, Big data
Depositing User: Ms Sharifah Fahimah Saiyed Yeop
Date Deposited: 26 Mar 2022 03:22
Last Modified: 26 Mar 2022 03:22
URI: http://scholars.utp.edu.my/id/eprint/31551

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