Query Expansion in Information Retrieval for Urdu Language

Abstract

The information retrieval system need to be upgraded constantly to meet the challenges posed by the advanced user queries as the search system becoming more sophisticated with time. These problems have been addressed extensively in recent times in several research communities to achieve quick and relevant outcome. One such approach is to augment the query where the automatic query expansion increases the precision in information retrieval even if it can cut down the results for some queries. Here, the above approach was tested with the present Urdu data collection obtained via different expansion models such as KL, Bo1 and Bo2. The current collection is quite large in size compared to other existing Urdu datasets. It comprises of 85,304 documents in a TRECschemes and 52 topics with their relevance assessment. In this paper we emphasize to enhance the retrieval model using the query expansion which is never done before on Urdu text. However, we show that a deep analysis of initial and expanded queries brings fascinating insights that could avail future research in the domain.