Fuzzy knowledge based performance analysis on big data

2020 ◽  
Vol 389 ◽  
pp. 218-228
Author(s):  
Neha Bharill ◽  
Aruna Tiwari ◽  
Aayushi Malviya ◽  
Om Prakash Patel ◽  
Akahansh Gupta ◽  
...  
Big Data ◽  
2016 ◽  
pp. 711-733 ◽  
Author(s):  
Jafreezal Jaafar ◽  
Kamaluddeen Usman Danyaro ◽  
M. S. Liew

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.


Author(s):  
Jafreezal Jaafar ◽  
Kamaluddeen Usman Danyaro ◽  
M. S. Liew

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.


2018 ◽  
Vol 7 (3.33) ◽  
pp. 168
Author(s):  
Yonglak SHON ◽  
Jaeyoung PARK ◽  
Jangmook KANG ◽  
Sangwon LEE

The LOD data sets consist of RDF Triples based on the Ontology, a specification of existing facts, and by linking them to previously disclosed knowledge based on linked data principles. These structured LOD clouds form a large global data network, which provides a more accurate foundation for users to deliver the desired information. However, it is difficult to identify that, if the presence of the same object is identified differently across several LOD data sets, they are inherently identical. This is because objects with different URIs in the LOD datasets must be different and they must be closely examined for similarities in order to judge them as identical. The aim of this study is that the prosed model, RILE, evaluates similarity by comparing object values of existing specified predicates. After performing experiments with our model, we could check the improvement of the confidence level of the connection by extracting the link value.  


1995 ◽  
Vol 45 (2) ◽  
pp. 135-143 ◽  
Author(s):  
Terhi Siimes ◽  
Pekka Linko ◽  
Camilla von Numers ◽  
Mikio Nakajima ◽  
Isao Endo

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