Personalized Web search offers a promising solution to the task of user-tailored information-seeking, and particularly in cases where the same query may represent diverse information needs. A significant component of any Web search personalization model is the means with which to model a user's interests and preferences to build what is termed as a user profile. This work explores the use of the Twitter microblog network as a source of user profile construction for Web search personalization. We propose a statistical language modeling approach taking into account various features of a user's Twitter network. The richness of the Web search personalization model leads to significant performance improvements in retrieval accuracy. Furthermore, the model is extended to include a similarity measure which further improves search engine performance. © 2014 Springer International Publishing Switzerland.
CITATION STYLE
Younus, A., O’Riordan, C., & Pasi, G. (2014). A language modeling approach to personalized search based on users’ microblog behavior. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8416 LNCS, pp. 727–732). Springer Verlag. https://doi.org/10.1007/978-3-319-06028-6_83
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