C4.5: programs for machine learning
C4.5: programs for machine learning
ACM SIGIR Forum
Query type classification for web document retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
Automatic identification of user goals in Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Determining the informational, navigational, and transactional intent of Web queries
Information Processing and Management: an International Journal
A Web Search Analysis Considering the Intention behind Queries
LA-WEB '08 Proceedings of the 2008 Latin American Web Conference
Automatic query type identification based on click through information
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
The intention behind web queries
SPIRE'06 Proceedings of the 13th international conference on String Processing and Information Retrieval
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In this work we explore the use of decision trees to identify the intent of a user query, based on informational, navigational, and transactional categorization. They are based on decision trees, using the C4.5 implementation. The classifier will be built from a query data set larger than any previously used, allowing the conclusions to have a greater reach. Unlike previous works, we will explore features that have not been evaluated before (e.g. PageRank) combined with features based on text and/or click-through data. The results obtained are very precise and the decision tree obtained allows us to illustrate relations among the variables used for classification determining which of these variables are more useful in the classification process.