Intent-Based Categorization of Search Results Using Questions from Web Q&A Corpus
Web Information Systems Engineering - WISE 2009, (2009)Abstract
User intent is defined as a user’s information need. Detecting intent in Web search helps users to obtain relevant content,
thus improving their satisfaction. We propose a novel approach to instantiating intent by using adaptive categorization producingpredicted intent probabilities. For this, we attempt to detect factors by which intent is formed, called intent features,by using a Web Q&A corpus. Our approach was motivated by the observation that questions related to queries are effective forfinding intent features. We extract set of categories and their intent features automatically by analyzing questions withinWeb Q&A corpus, and categorize search results using these features. The advantages of our intent-based categorization aretwofold, (1) presenting the most probable intent categories to help users clarify and choose starting points for Web searches,and (2) adapting sets of intent categories for each query. Experimental results show that distilled intent features can efficientlydescribe intent categories, and search results can be efficiently categorized without any human supervision.
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