An Integrated Search Framework for Leveraging the Knowledge-Based Web Ecosystem

TL;DR

This paper introduces an Integrated Search Framework (ISF) that combines multiple search technologies to enhance information retrieval across various knowledge-based web environments, demonstrating improved precision over existing search engines.

Contribution

The paper presents a novel ISF that integrates crawling, web search, and database search methods for personalized and organization-oriented retrieval in KBWE scenarios.

Findings

Improved search precision compared to popular engines

Effective management of diverse search results

Enhanced retrieval in KBWE environments

Abstract

The explosion of information constrains the judgement of search terms associated with Knowledge-Based Web Ecosystem (KBWE), making the retrieval of relevant information and its knowledge management challenging. The existing information retrieval (IR) tools and their fusion in a framework need attention, in which search results can effectively be managed. In this article, we demonstrate the effective use of information retrieval services by a variety of users and agents in various KBWE scenarios. An innovative Integrated Search Framework (ISF) is proposed, which utilises crawling strategies, web search technologies and traditional database search methods. Besides, ISF offers comprehensive, dynamic, personalized, and organization-oriented information retrieval services, ranging from the Internet, extranet, intranet, to personal desktop. In this empirical research, experiments are carried out demonstrating the improvements in the search process, as discerned in the conceptual ISF. The experimental results show improved precision compared with other popular search engines.