Automatic Concept-Based Query Expansion Using Term Relational Pathways Built from a Collection-Specific Association Thesaurus

Abstract

The dissertation research explores an approach to automatic concept-based query expansion to improve search engine performance. It uses a network-based approach for identifying the concept represented by the user's query and is founded on the idea that a collection-specific association thesaurus can be used to create a reasonable representation of all the concepts within the document collection as well as the relationships these concepts have to one another. Because the representation is generated using data from the association thesaurus, a mapping will exist between the representation of the concepts and the terms used to describe these concepts. The research applies to search engines designed for use in an individual website with content focused on a specific conceptual domain. Therefore, both the document collection and the subject content must be well-bounded, which affords the ability to make use of techniques not currently feasible for general purpose search engine used on the entire web.