Search result summarization and disambiguation via contextual dimensions
Krishna Prasad Chitrapura, Sachindra Joshi, Raghu J. Krishnapuram · 2006
Topic hierarchies are a popular method of summarizing the results obtained in response to a query in various search applications. However, topic hierarchies are rigid when they are pre-defined and somewhat unintuitive when they are dynamically generated by statistical techniques. In this paper, we propose an alternative approach to query disambiguation and result summarization by placing the results in set of contextual dimensions which can be viewed as facets. For the generic search scenario, we illustrate our approach by using three types of contextual dimensions, namely, concepts, features, and specializations. We use NLP techniques and a data mining algorithm to select distinct contexts.