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What is Satisfiablility

Chapter 5
Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence
In this chapter, satisfiablity is the ability of the Web data concepts that are be able to test the value of the semantic query of atomic concepts. Similarly, satisfiability determines the variables of the given boolean.
Published in Chapter:
Web Intelligence: A Fuzzy Knowledge-Based Framework for the Enhancement of Querying and Accessing Web Data
Jafreezal Jaafar (Universiti Teknologi PETRONAS, Malaysia), Kamaluddeen Usman Danyaro (Universiti Teknologi PETRONAS, Malaysia), and M. S. Liew (Universiti Teknologi PETRONAS, Malaysia)
Copyright: © 2015 |Pages: 22
DOI: 10.4018/978-1-4666-8505-5.ch005
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.
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