Toward an Enhancement of Textual Database Retrieval Using NLP Techniques

• Authors: Asanee Kawtrakul;Frédéric Andrès;Kinji Ono;Chaiwat Ketsuwan;Nattakan Pengphon
• Venue: NLDB '00 Proceedings of the 5th International Conference on Applications of Natural Language to Information Systems-Revised Papers
• Year: 2000

Improvements in hardware, communication technology and database have led to the explosion of multimedia information repositories. In order to improve the quality of information retrieval compared to already existing advanced document management systems, research works have shown that it is necessary to consider vertical integration of retrieval techniques inside database service architecture. This paper focuses on the integration of NLP techniques for efficient textual database retrieval as part of the VLSHDS Project -Very Large Scale Hypermedia Delivery System. One target of this project is to increase the quality of textual information search (precision/recall) compared to already existing multi-lingual IR systems by applying morphological analysis and shallow parsing in phrase level to document and query processing. The scope of this paper is limited to Thai documents. The underlying system is The Active HYpermedia Delivery System-(AHYDS) framework providing the delivery service over internet. Based on 1100 Thai documents, as first results, our approach improved the precision and recall from 72.666% and 56.67% in the initial implementation (without applying NLP techniques) to 85.211% and 76.876% respectively.