Turning WordNet into an Information Retrieval Resource: Systematic Polysemy and Conversion to Hierarchical Codes
Rada F. Mihalcea · International Journal of Pattern Recognition and Artificial Intelligence · 2003
This paper addresses the problem of transforming WordNet into a resource tailored to Information Retrieval (IR) applications. We address two of the major drawbacks pointed out in previous literature in relation to this semantic network. One is the fine granularity of senses defined in WordNet, which proves useless from an IR perspective. To solve this problem, we propose a set of methods that enable the automatic transformation of WordNet into a coarse grained dictionary. The other drawback is the encoding used in this resource, and the methods for accessing related words across the semantic net. Due to the high number of connections among concepts, the simple computation of a path in this net, or the generation of related concepts may become a computationally intensive process. This effect is highly undesirable in time sensitive applications such as IR applications. We propose a methodology for hierarchical encoding that enables increased efficiency in WordNet-based IR systems.