Conceptual Structures in Modern Information Retrieval

Abstract

Motivated by a desire to go beyond keywords, the use of conceptual structures to improve the effectiveness of information retrieval has been around for a long time without producing impressive results. However, things have changed considerably over the last few years. The growth of the web has favoured the emergence of new search applications, usage patterns, data formats, and interaction paradigms. Traditional information retrieval assumptions and techniques have thus been deeply questioned; for instance, it is inherently more difficult to retrieve the information of interest if the user queries are very short and the collections being searched are highly heterogeneous, as is the case in web retrieval. Furthermore, a number of more challenging information finding tasks have emerged that seem to require a better understanding of the meaning of queries and documents and at least some ability of interpretation and manipulation of text data. These include, among others, question answering, information retrieval with structured queries, homepage finding, information retrieval from mobile devices, recommender systems, and mining of specialised collections. As a result, much of the current research in information retrieval has focused on the exploitation of a richer query or document context, from which to extract concepts or knowledge that may improve the system’s retrieval effectiveness. Retrieval feedback, ontologies, XML, and web links are popular examples of a contextual source used for enhanced information retrieval.