![](bg8.png)
Research and development in information retrieval,
pages 299–306. ACM.
Dou, Z., Song, R., and Wen, J.-R. (2007). A large-scale
evaluation and analysis of personalized search strate-
gies. In Proceedings of the 16th international confer-
ence on World Wide Web, pages 581–590. ACM.
Harvey, M., Crestani, F., and Carman, M. J. (2013). Build-
ing user profiles from topic models for personalised
search. In Proceedings of the 22nd ACM international
conference on Conference on information & knowl-
edge management, pages 2309–2314. ACM.
Hofmann, T. (1999). Probabilistic latent semantic analysis.
In Proceedings of the Fifteenth conference on Uncer-
tainty in artificial intelligence, pages 289–296. Mor-
gan Kaufmann Publishers Inc.
Karimi-Mansoub, S. and Abri, R. (2016). Improvement of
semantic search results with providing an updatable
dynamic user model. International Journal of Com-
puter Applications, 155(4):7–14.
Manning, C. D., Raghavan, P., and Hinrich, S. (2008). In-
troduction to information retrieval. In Introduction to
Information Retrieval. Cambridge University Press.
Matthijs, N. and Radlinski, F. (2011). Personalizing web
search using long term browsing history. In Proceed-
ings of the fourth ACM international conference on
Web search and data mining, pages 25–34. ACM.
Momtazi, S. and Lindenberg, F. (2016). Generating query
suggestions by exploiting latent semantics in query
logs. In Journal of Information Science, pages 437–
448. ACM.
Shao, M. and Qin, L. (2014). Text similarity computing
based on lda topic model and word co-occurrence. In
2nd International Conference on Software Engineer-
ing, Knowledge Engineering and Information Engi-
neering (SEKEIE 2014).
Siegg, A., Mobasher, B., and Burke, R. (2007). Web search
personalization with ontological user profiles. In Pro-
ceedings of the ACM Conference on information and
knowledge management, pages 525–534. ACM.
Song, R., Luo, Z., Wen, J.-R., Yu, Y., and Hon, H.-W.
(2007). Identifying ambiguous queries in web search.
In Proceedings of the 16th international conference on
World Wide Web, pages 1169–1170. ACM.
Teevan, J., Dumais, S., and Horvitz, E. (2005). Beyond
the commons: Investigating the value of personaliz-
ing web search. In Proceedings of the Workshop on
New Technologies for Personalized Information Ac-
cess (PIA), pages 84–92.
Teevan, J., Dumais, S., and Horvitz, E. (2010). Potential for
personalization. In ACM Transactions on Computer-
Human Interaction (TOCHI) TOCHI, pages 1–31.
ACM.
Teevan, J., Dumais, S. T., and Liebling, D. J. (2008). To
personalize or not to personalize: modeling queries
with variation in user intent. In Proceedings of the
31st annual international ACM SIGIR conference on
Research and development in information retrieval,
pages 163–170. ACM.
Vu, T., Willis, A., Kruschwitz, U., and Song, D. (2017).
Personalised query suggestion for intranet search with
temporal user profiling. In Proceedings of the 2017
Conference on Conference Human Information Inter-
action and Retrieval, pages 265–268. ACM.
Vu, T. T., Willis, A., and Song, D. (2015a). Modelling
time-aware search tasks for search personalisation. In
Proceedings of the 24th International Conference on
World Wide Web, pages 131–132. ACM.
Vu, T. T., Willis, A., Tran, S., and Song, D. (2015b). Tempo-
ral latent topic user profiles for search personalisation.
In ECIR:37th European Conference on IR Research,
pages 605–616. ACM.
Wang, Y. and Agichtein, E. (2010). Query ambiguity re-
visited: clickthrough measures for distinguishing in-
formational and ambiguous queries. In HLT ’10 Hu-
man Language Technologies: The 2010 Annual Con-
ference of the North American Chapter of the Associ-
ation for Computational Linguistics, pages 361–364.
ACM.
Wei, S., Yu, Z., Ting, L., and Sheng, L. (2010). Bridging
topic modeling and personalized search. In Proceed-
ings of the 23rd International Conference on Com-
putational Linguistics: Posters, pages 1167–1175.
ACM.
Yano, Y., Tagami, Y., and Tajima, A. (2016). Quantifying
query ambiguity with topic distributions. In Proceed-
ings of the 25th ACM International on Conference
on Information and Knowledge Management, pages
1877–1880. ACM.
KDIR 2020 - 12th International Conference on Knowledge Discovery and Information Retrieval
152