Abstract
Recent work on analyzing query logs shows that a significant fraction of queries are temporal, i.e., relevancy is dependent on time, and temporal queries play an important role in many domains, e.g., digital libraries and document archives. Temporal queries can be divided into two types: 1) those with temporal criteria explicitly provided by users, and 2) those with no temporal criteria provided. In this paper, we deal with the latter type of queries, i.e., queries that comprise only keywords, and their relevant documents are associated to particular time periods not given by the queries. We propose a number of methods to determine the time of queries using temporal language models. After that, we show how to increase the retrieval effectiveness by using the determined time of queries to re-rank the search results. Through extensive experiments we show that our proposed approaches improve retrieval effectiveness.
This work has been supported by the LongRec project, partially funded by the Norwegian Research Council.
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References
Berberich, K., Bedathur, S., Alonso, O., Weikum, G.: A language modeling approach for temporal information needs. In: Proceedings of ECIR 2010 (2010)
Berberich, K., Bedathur, S.J., Neumann, T., Weikum, G.: A time machine for text search. In: Proceedings of SIGIR 2007 (2007)
de Jong, F., Rode, H., Hiemstra, D.: Temporal language models for the disclosure of historical text. In: Proceedings of AHC 2005 (History and Computing) (2005)
Diaz, F., Jones, R.: Using temporal profiles of queries for precision prediction. In: Proceedings of the 27th SIGIR (2004)
Jatowt, A., Kawai, Y., Tanaka, K.: Temporal ranking of search engine results. In: Ngu, A.H.H., Kitsuregawa, M., Neuhold, E.J., Chung, J.-Y., Sheng, Q.Z. (eds.) WISE 2005. LNCS, vol. 3806, pp. 43–52. Springer, Heidelberg (2005)
Kanhabua, N., Nørvåg, K.: Improving temporal language models for determining time of non-timestamped documents. In: Christensen-Dalsgaard, B., Castelli, D., Ammitzbøll Jurik, B., Lippincott, J. (eds.) ECDL 2008. LNCS, vol. 5173, pp. 358–370. Springer, Heidelberg (2008)
Kraaij, W.: Variations on language modeling for information retrieval. SIGIR Forum 39(1), 61 (2005)
Li, X., Croft, W.B.: Time-based language models. In: Proceedings of CIKM (2003)
Metzler, D., Jones, R., Peng, F., Zhang, R.: Improving search relevance for implicitly temporal queries. In: Proceedings of SIGIR 2009 (2009)
Nørvåg, K.: Supporting temporal text-containment queries in temporal document databases. Journal of Data & Knowledge Engineering 49(1), 105–125 (2004)
Nunes, S., Ribeiro, C., David, G.: Use of temporal expressions in web search. In: Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., White, R.W. (eds.) ECIR 2008. LNCS, vol. 4956, pp. 580–584. Springer, Heidelberg (2008)
Perkiö, J., Buntine, W., Tirri, H.: A temporally adaptive content-based relevance ranking algorithm. In: Proceedings of the 28th SIGIR (2005)
Sato, N., Uehara, M., Sakai, Y.: Temporal ranking for fresh information retrieval. In: Proceedings of the 6th IRAL (2003)
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Kanhabua, N., Nørvåg, K. (2010). Determining Time of Queries for Re-ranking Search Results. In: Lalmas, M., Jose, J., Rauber, A., Sebastiani, F., Frommholz, I. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2010. Lecture Notes in Computer Science, vol 6273. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15464-5_27
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DOI: https://doi.org/10.1007/978-3-642-15464-5_27
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