Web intelligence: A fuzzy knowledge-based framework for the enhancement of querying and accessing web data
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 th...
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| Main Authors: | , , |
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| Format: | Book |
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IGI Global
2015
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84957367348&doi=10.4018%2f978-1-4666-8505-5.ch005&partnerID=40&md5=b43f08c01751a209727245fe33c5e4e1 http://eprints.utp.edu.my/31551/ |
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| Summary: | 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. |
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