An Agent based Approach towards Metadata Extraction, Modelling and Information Retrieval over the Web

TL;DR

This paper proposes an agent-based approach to improve metadata extraction, modeling, and information retrieval on the web, aiming to enhance semantic understanding and search efficiency in complex web data environments.

Contribution

It introduces a novel agent-based framework for semantic metadata extraction and retrieval, addressing limitations in current full-text search mechanisms.

Findings

Enhanced semantic understanding in web data retrieval

Improved accuracy in metadata extraction

Potential for more efficient knowledge-based searches

Abstract

Web development is a challenging research area for its creativity and complexity. The existing raised key challenge in web technology technologic development is the presentation of data in machine read and process able format to take advantage in knowledge based information extraction and maintenance. Currently it is not possible to search and extract optimized results using full text queries because there is no such mechanism exists which can fully extract the semantic from full text queries and then look for particular knowledge based information.