Identifying the intent of a user query using support vector machines

Marcelo Mendoza, Juan Zamora

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

18 Citas (Scopus)

Resumen

In this paper we introduce a high-precision query classification method to identify the intent of a user query given that it has been seen in the past based on informational, navigational, and transactional categorization. We propose using three vector representations of queries which, using support vector machines, allow past queries to be classified by user's intents. The queries have been represented as vectors using two factors drawn from click-through data: the time users take to review the documents they select and the popularity (quantity of preferences) of the selected documents. Experimental results show that time is the factor that yields higher precision in classification. The experiments shown in this work illustrate that the proposed classifiers can effectively identify the intent of past queries with high-precision.

Idioma originalInglés
Título de la publicación alojadaString Processing and Information Retrieval - 16th International Symposium, SPIRE 2009, Proceedings
Páginas131-142
Número de páginas12
DOI
EstadoPublicada - 2009
Publicado de forma externa
Evento16th International Symposium on String Processing and Information Retrieval, SPIRE 2009 - Saariselka, Finlandia
Duración: 25 ago. 200927 ago. 2009

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen5721 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia16th International Symposium on String Processing and Information Retrieval, SPIRE 2009
País/TerritorioFinlandia
CiudadSaariselka
Período25/08/0927/08/09

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