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SPS: A Web Content Search System Utilizing Semantic Processing

Authors:
Joseph Leone
Dong-Guk Shin

Keywords: Keywords-Web content mining; semantic processing; dynamic ontology development; collaboration system; information retrieval; biomedical literature mining

Abstract:
This paper describes a Web content search system that employs semantic processing. The system, called SPS (semantic processing system), consists of a crowd-sourced ontology, a component for updating and extending the ontology, an NL parser, a semantic matcher, and a content representation formalism called semantic processing (SP) logical form. A typical web search results in hundreds of pages. The user then carries out the tedious and daunting task of sifting through each page to find the relevant/interesting information. SPS aims to improve the relevance by building a layer of automated filtering on top of conventional search engines. SPS takes a user’s natural language query, composes it into a keyword query, augments the keyword query with additional keywords, and presents it to the search engine. The query when augmented with additional keywords produces a richer search result set. SPS sifts through each search result page extracting grammatical and semantic information to compute page relevance. We present the architectural framework for SPS and also illustrate how it uses semantic processing to improve the quality of search results.

Pages: 48 to 53

Copyright: Copyright (c) IARIA, 2011

Publication date: September 25, 2011

Published in: conference

ISSN: 2308-4162

ISBN: 978-1-61208-157-1

Location: Rome, Italy

Dates: from September 25, 2011 to September 30, 2011