ONTOLOGICAL APPROACH FOR IMPROVING SEMANTIC WEB SEARCH RESULTS

Improving Web Search Results Using Semantic Clustering

This paper consider the problem of search engine that are not capable of retrieving appropriate result on query given. Most of the users are not able to give the appropriate query to get what exactly they wanted to retrieve. So the search engine retrieves a massive list of data, which are ranked by the page rank algorithm or relevancy algorithm or human judgment algorithm. If the relevant resul...

Improving Search Results with Lightweight Semantic Search

The goal of each search service is to yield the most relevant results on a given query. Traditional full-text search is not enough and many approaches to improve search rankings are adopted. In this paper we propose a method of combined search query scoring computation leveraging lightweight semantics represented by metadata related to searchable content. It extends state-of-the-art approaches ...

Semantic Transformation of Search Requests for Improving the Results of Web Search

The paper describes a new method of constructing semantic expansions of search requests for improving the results of Web search. This method is based on the theory of K-representations a new theory of designing semantic-syntactic analyzers of natural language texts with the broad use of formal means for representing input, intermediary, and output data. The current version of the theory is set ...

A Study of Meta-Search Agent Based on Tags and Ontological Approach for Improving Web Searches

Semantic Web Search Based on Ontological Conjunctive Queries

Many experts predict that the next huge step forward in Web information technology will be achieved by adding semantics to Web data, and will possibly consist of (some form of) the Semantic Web. In this paper, we present a novel approach to Semantic Web search, which allows for a semantic processing of Web search queries, and for evaluating complex Web search queries that involve reasoning over...