Designing a Dynamic Components and Agent based Approach for Semantic Information Retrieval

TL;DR

This paper introduces SOAS, a semantic web-based agent system designed to improve web information retrieval through automatic request handling, dynamic full-text analysis, and semantic query generation.

Contribution

It proposes a novel agent-based architecture with dynamic components for enhanced semantic information retrieval on the web.

Findings

Effective automatic user request processing

Dynamic full-text reading and analysis implemented

Semantic query generation improves retrieval accuracy

Abstract

In this paper based on agent and semantic web technologies we propose an approach .i.e., Semantic Oriented Agent Based Search (SOAS), to cope with currently existing challenges of Meta data extraction, modeling and information retrieval over the web. SOAS is designed by keeping four major requirements .i.e., Automatic user request handling, Dynamic unstructured full text reading, Analysing and modeling, Semantic query generation and optimized result classifier. The architecture of SOAS is consisting of an agent called Personal Agent (PA) and five dynamic components .i.e., Request Processing Unit (RPU), Agent Locator (AL), Agent Communicator (AC), List Builder (LB) and Result Generator (RG). Furthermore, in this paper we briefly discuss Semantic Web and some already existing in time proposed and implemented semantic based approaches.