Abstract
Web queries are time sensitive which implies that user’s intent for information changes over time. How to recognize temporal intents behind user queries is crucial towards improving the performance of search engines. However, to the best of our knowledge, this problem has not been studied in existing work. In this paper, we propose a time-based query classification approach to understand user’s temporal intent automatically. We first analyzed the shared features of queries’ temporal intent distributions. Then, we present a query taxonomy which group queries according to their temporal intents. Finally, for a new given query, we propose a machine learning method to decide its class in terms of its search frequency over time recorded in Web query logs. Experiments demonstrate that our approach can understand users’ temporal intents effectively.
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Ren, P., Chen, Z., Song, X., Li, B., Yang, H., Ma, J. (2013). Understanding Temporal Intent of User Query Based on Time-Based Query Classification. In: Zhou, G., Li, J., Zhao, D., Feng, Y. (eds) Natural Language Processing and Chinese Computing. NLPCC 2013. Communications in Computer and Information Science, vol 400. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41644-6_31
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DOI: https://doi.org/10.1007/978-3-642-41644-6_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41643-9
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