Ranking Search Intents Underlying a Query
Observation on query log of search engine indicates that queries are usually ambiguous. Similar to document ranking, search intents should be ranked to facilitate information search. Previous work attempts to rank intents with merely relevance score. We argue that diversity is also important. In this work, unified models are proposed to rank intents underlying a query by combining relevance score and diversity degree, in which the latter is reflected by non-overlapping ratio of every intent and aggregated non-overlapping ratio of a set of intents. Three conclusions are drawn according to the experiment results. Firstly, diversity plays an important role in intent ranking. Secondly, URL is more effective than similarity in detecting unique subtopics. Thirdly, the aggregated non-overlapping ratio makes some contribution in similarity based intent ranking but little in URL based intent ranking.
KeywordsIntent ranking relevance diversity non-overlapping ratio aggregated non-overlapping ratio
Unable to display preview. Download preview PDF.
- 1.Song, R., Zhang, M., Sakai, T., Kato, M., Liu, Y., Sugimoto, M., Wang, Q., Orii, N.: Overview of the NTCIR-9 INTENT Task. In: Proc. of NTCIR-9 Workshop Meeting, Tokyo, Japan, December 6-9, pp. 82–104 (2011)Google Scholar
- 2.Xue, Y., Chen, F., Zhu, T., Wang, C., Li, Z., Liu, Y., Zhang, M., Jin, Y., Ma, S.: THUIR at NTCIR-9 INTENT Task. In: Proc. of NTCIR-9, Tokyo, Japan, December 6-9 (2011)Google Scholar
- 3.Song, W., Zhang, Y., Gao, H., Liu, T., Li, S.: HITSCIR System in NTCIR-9 Subtopic Mining Task. In: Proc. of NTCIR-9, Tokyo, Japan, December 6-9 (2011)Google Scholar
- 4.Han, J., Wang, Q., Orii, N., Dou, Z., Sakai, T., Song, R.: Microsoft Research Asia at the NTCIR-9 Intent Task. In: Proc. of NTCIR-9, Tokyo, Japan, December 6-9 (2011)Google Scholar
- 5.Santos, R.L.T., Macdonald, C., Ounis, I.: University of Glasgow at the NTCIR-9 Intent task: Experiments with Terrier on subtopic mining and document ranking. In: Proc. of NTCIR-9, Tokyo, Japan, December 6-9 (2011)Google Scholar
- 6.Carbonell, J., Goldstein, J.: The use of MMR, diversity-based reranking for reordering documents and producing summaries. In: Proc. of SIGIR 1998, Melbourne, Australia, pp. 335–336 (1998)Google Scholar
- 7.Swaminathan, A., Mathew, C.V., Kirovski, D.: Essential Pages. In: Proc. of WI 2009, Milan, Italy, pp. 173–182 (2009)Google Scholar
- 8.Santamaría, C., Gonzalo, J., Artiles, J.: Wikipedia as sense inventory to improve diversity in web search results. In: Proc. of ACL 2010, Uppsala, Sweden, pp. 1357–1366 (2010)Google Scholar
- 9.Brody, S., Lapata, M.: Bayesian word sense induction. In: Proc. of EACL 2009, pp. 103–111 (2009)Google Scholar
- 10.Dueck, D.: Affinity Propagation: Clustering Data by Passing Messages. University of Toronto Ph.D. thesis (June 2009)Google Scholar