A Comparative Study of Semantic Search Systems

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Date

2020

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IEEE

Abstract

Today’s internet consists of mostly unstructured data, most of it being unusable for average users. With increase in the number of smart devices that are getting access to the web, we have a large set of unlinked data that is not able to communicate. Indirectly, it can be said that the Web is broken. Semantic Web focuses on making the meaning explicit instead of fetching results with the help of word matching. Semantic Web is an extension to the current Web that provides an easier way to find, share, reuse and combine information. In this paper, we are presenting an analysis of the different approaches taken by various semantic web search engines and the comparison between them, thus identifying the advantages and limitation of each search engine.

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Keywords

Computer Science, Semantic Search, Large Datasets, Dot-com Bubble, Ontology Language

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