Natural Language Query Refinement Scheme for Indic Literature Information System on Mobiles

The concept and realization of 'Information Pulling' on handheld mobile devices facilitate an easy and effective information access. SMS driven English language information systems for various domains like agriculture, health, education, banking and government are available. However, information systems that support Indic languages are not reported. We have developed an information system that retrieves appropriate transliterated literature documents of Marathi and Hindi languages in response to SMS queries. The proposed system uses Vector Space Model (VSM) to rank the documents according to similarity score. We proposed and used appropriate data structures to enhance the basic VSM for the transliterated document domain. Furthermore we propose to customize the rank of the results obtained in response to user queries. The rank management is based on corresponding relevance feedback given by users. In this paper we describe the development of the information system for transliterated documents and share our experimental results of relevance feedback mechanism. We have designed a probability relevance model for rank management customization. The performance improvement of the system is demonstrated with the help of standard measures Normalized Discounted Cumulative Gain (NDCG) and Discounted Cumulative Gain (DCG).