Abstract
Previous studies in Information Retrieval literature have shown that users’ search history can be leveraged to improve current search results. However sometimes we have little to no search history available. In such cases, it would be helpful to obtain data similar to search history data. One way of doing this is by simulating previous search interactions. In the present study, we focus on generating simulated “related queries” that can serve as an additional source of information about the current search [1]. Assuming that users reformulate their queries by leveraging some of the terms and key phrases they find in ranked documents during their search, we proposed simple models for generating such related queries.
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Bah, A., Carterette, B.: Aggregating results from multiple related queries to improve web search over sessions. In: Jaafar, A., et al. (eds.) AIRS 2014. LNCS, vol. 8870, pp. 172–183. Springer, Heidelberg (2014)
Baskaya, F.: Simulating Search Sessions in Interactive Information Retrieval Evaluation. Tampere University, Tampere (2014)
Baskaya, F., Keskustalo, H., Järvelin, K.: Simulating simple and fallible relevance feedback. In: Clough, P., Foley, C., Gurrin, C., Jones, G.J., Kraaij, W., Lee, H., Mudoch, V. (eds.) ECIR 2011. LNCS, vol. 6611, pp. 593–604. Springer, Heidelberg (2011)
Baskaya, F., Keskustalo, H., Järvelin, K.: Time drives interaction: simulating sessions in diverse searching environments. In: Proceedings of SIGIR, August 2012
Carterette, B., Bah, A., Zengin, M.: Dynamic test collections for retrieval evaluation. In: Proceedings of the 2015 International Conference on the Theory of Information Retrieval, pp. 91–100. ACM, September 2015
Carterette, B., Kanoulas, E., Hall, M.M., Clough, P.D.: Overview of the TREC 2013 Session Track. In: TREC (2013)
Cormack, G.V., Smucker, M.D., Clarke, C.L.: Efficient and effective spam filtering and re-ranking for large web datasets. Inf. Retr. 14(5), 441–465 (2011)
Guan, D.: Structured Query Formulation and Result Organization for Session Search (Doctoral dissertation, Georgetown University) (2013)
Guan, D., Zhang, S., Yang, H.: Utilizing query change for session search. In: Proceedings of SIGIR, July 2013
Järvelin, K., Kekäläinen, J.: Cumulated gain-based evaluation of IR techniques. ACM Trans. Inf. Syst. (TOIS) 20(4), 422–446 (2002)
Jiang, J., He, D., Han, S.: On duplicate results in a search session. In: Proceedings of the 21st TREC (2012)
Keskustalo, H., Järvelin, K., Pirkola, A., Sharma, T., Lykke, M.: Test collection-based IR evaluation needs extension toward sessions – a case of extremely short queries. In: Lee, G.G., Song, D., Lin, C.-Y., Aizawa, A., Kuriyama, K., Yoshioka, M., Sakai, T. (eds.) AIRS 2009. LNCS, vol. 5839, pp. 63–74. Springer, Heidelberg (2009)
Kruschwitz, U.: University of essex at the TREC 2012 session track. In: Proceedings of the 21st TREC (2012)
Raman, K., Bennett, P.N., Collins-Thompson, K.: Toward whole-session relevance: exploring intrinsic diversity in web search. In: Proceedings of the 36th International ACM SIGIR, pp. 463–472. ACM, July 2013
Strohman, T., Metzler, D., Turtle, H., Croft, W.B.: Indri: a language model-based search engine for complex queries. In: Proceedings of the International Conference on Intelligent Analysis, vol. 2, no. 6, pp. 2–6, May 2005
Verberne, S., Sappelli, M., Järvelin, K., Kraaij, W.: User simulations for interactive search: evaluating personalized query suggestion. In: Hanbury, A., Kazai, G., Rauber, A., Fuhr, N. (eds.) ECIR 2015. LNCS, vol. 9022, pp. 678–690. Springer, Heidelberg (2015)
Yahoo! BOSS. https://developer.yahoo.com/search/boss/
Zhang, S., Guan, D., Yang, H.: Query change as relevance feedback in session search. In: Proceedings of the 36th International ACM SIGIR Conference, pp. 821–824. ACM, July 2013
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Bah, A., Carterette, B. (2016). Generating Pseudo Search History Data in the Absence of Real Search History. In: Hartmann, S., Ma, H. (eds) Database and Expert Systems Applications. DEXA 2016. Lecture Notes in Computer Science(), vol 9828. Springer, Cham. https://doi.org/10.1007/978-3-319-44406-2_34
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DOI: https://doi.org/10.1007/978-3-319-44406-2_34
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