Improving Arabic Information Retrieval Systems Using Part of Speech Tagging

Abstract

The objective of Information Retrieval is to retrieve all relevant documents for a user query and only those relevant documents. Much research has focused on achieving this objective with little regard for storage overhead or performance. In this paper we evaluate the use of Part of Speech Tagging to improve the index storage overhead and general speed of the system with only a minimal increment in precision and recall measurements. We tagged 242 abstracts of Arabic documents using the Proceedings of the Saudi Arabian National Conferences as a source. All these abstracts involve computer science.. We also built an automatic information retrieval system to handle Arabic data. We then did a series of experiments to identify the most relevant part of speech indexing method.