Information Retrieval in Expert Matching System - IREMS

Abstract

The Internet is a vital source to disseminate and share information to the masses. This has made information available in abundance on the Web. People have realized the need and importance of relevant and precise information when data is in abundance. Communication is increasing with such a rapid pace that people not only desire to acquire a lot of information but also relevant information. Information is present on the Web but to retrieve explicit information is a hard job because most of the people who are looking for relevant information (information seekers) are not aware of the ways through which explicit and to the point information can be acquired. This gives rise to the need of relevant information retrieval. However, finding relevant information is difficult if not impossible. This difficulty is bilateral between information providers and seekers in terms of information presentation and accessibility respectively. Information presentation deals with the format and layout of the information that is being presented in front of the seekers. While, information accessibility is concerned to acquire information at any time and at any place and this is only possible through an online system. Information presentation is managed by using a pre-defined template that presents information in a consistent and standard format. Now the main issue is to search the required information with maximum relevancy to the search criteria. The percentage of relevance searching can only be enhanced by using techniques that can link concepts with each other instead of just matching exact keywords which results in more data that is less relevant as well. Unlike keyword search systems that match exactly what you “say” (or what you type), concept search systems strive to determine what you mean. Concept search engines aim to do what you do naturally in conversations with others i.e. account for the different ways people express the same idea. Mere keyword searching does not increase the percentage of relevance searching as it only match exact literals and this give rise to semantic heterogeneity in information retrieval. Hence concept searching is added to it which links concepts with each other based on the ontology provided to link the concepts. This makes information retrieval efficient effective. Along with this the system must also be highly scalable and self-organizing that helps individuals in presenting and accessing the information in a consistent format on the Web. This makes the sharing of information among the autonomous organizations successful.