A Computational Modeling for Knowledge Binding of the Unstructured Web Data
Patil N S1, Kiran P2, Preethi B3
1Patil N S, Assistant Professor, Department of Information Science, BIET, Davangere (Karnataka), India.
2Dr. Kiran, Associate Professor, Department of CSE, RNSIT, Bengaluru (Karnataka), India.
3Preethi B, Assistant Professor, Department of Computer Science, BIET, Davangere (Karnataka), India.
Manuscript received on 05 December 2019 | Revised Manuscript received on 13 December 2019 | Manuscript Published on 31 December 2019 | PP: 418-424 | Volume-9 Issue-2S December 2019 | Retrieval Number: B10411292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1041.1292S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The focus of this manuscript is laid towards extracting insightful data embedded into web-based information which is crucial for various academic and commercialized application requirements. The study thereby introduces a robust computational modeling by means of computing knowledge from collaborative web-based unstructured information. For this purpose, this design is simplified with Fuzzy based matching algorithm and also with a set of procedures which reduces the computational effort to a significant extent. The numerical theoretical analysis shows that the effectiveness of the formulated model. It also shows that the formulated concept outperforms the baseline modeling by almost 50% when computational performance is concerned.
Keywords: Unstructured Web-Data, Fuzzy Logic, Information Mining.
Scope of the Article: Semantic Web