Abstract
With the exponential growth in web content and due to its sheer volume, the answers provided by traditional search engines by query specific keywords to content has resulted in markedly high recall and low precision. In order to alleviate this problem, the notion of incorporating semantics in content and in Search Engines, i.e., a Semantic Search Engine is increasingly crucial. Several Semantic Search Engines (SSEs) have been proposed and deployed till date and each is inherently different from the other. As such, the objective of this paper is to present a discussion on semantically enhanced search engines for intelligent web content discovery. We also present the architecture of a new SSE based on a bottom up approach that focuses on building a semantic base for Web content first and then carry out the process of querying it for attaining high precision and lower recall.
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