Query Expansion Using an Intranet-based Semantic Net

Many of today’s web search engine users submit single word queries resulting in an imprecise and overwhelming result set. This paper describes the implementation of a query expansion application prototype, i.e., a tool to augment the original query with more, and hopefully, relevant terms. The prototype uses a semantic net to represent relationships between words and concepts used on a corporate intranet. The aim has been to increase precision and prevent receiving too many documents. The result, compared to that of an unmodified search, shows a gain in precision at the cost of lower recall. Another major thing the experiment teaches us is that the knowledge acquisition cost required to manually build the semantic net may be too high. The paper closes with a discussion about the pros and cons of a query expansion program such as a semantic net.