Time is an important factor that needs to be considered in information retrieval. Often queries raised to search engines may have temporal intention, or the search results that the user interests are time-dependent. In this paper, we deal with one type of temporal queries – implicitly temporal queries. Those queries do not contain explicitly temporal expressions, but the user’s information need is related to time. For a given query, we analyze its temporal intention and set up two linear combination models. One of them is based on the language modeling, and the other is based on the metric space model. Both of them consider both aspects of content and time to rank all the documents involved. Experiment results with the dataset that was used in the Temporal Information Access task of NTCIR-11 show that our approaches are effective.
CITATION STYLE
Wang, J., & Wu, S. (2017). Information retrieval with implicitly temporal queries. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10585 LNCS, pp. 103–111). Springer Verlag. https://doi.org/10.1007/978-3-319-68935-7_12
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