In International Workshop on Query Understanding and Reformulation for Mobile and Web Search collocated with The 9th ACM International Conference on Web Search and Data Mining , 2016-03-22

Title : ( Query Expansion Using Pseudo Relevance Feedback on Wikipedia )

Authors: Andisheh Keykhah , F Ensan , Ebrahim Bagheri ,

Citation: BibTeX | EndNote

One of the major challenges in Web search pertains to the correct interpretation of users' intent. Query Expansion is one of the well-known approaches for determining the intent of the user by addressing the vocabulary mismatch prob- lem. A limitation of the current query expansion approaches is that the relations between the query terms and the expanded terms is limited. In this paper, we capture users' intent through query expansion. We build on earlier work in the area by adopting a pseudo-relevance feedback approach; however, we advance the state of the art by proposing an approach for feature learning within the process of query expansion. In our work, we speci cally consider the Wikipedia corpus as the feedback collection space and identify the best features within this context for term selection in two supervised and unsupervised models. We compare our work with state of the art query expansion techniques, the results of which show promising robustness and improved precision.

Keywords

Query Expansion Using Pseudo Relevance Feedback on
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@inproceedings{paperid:1053424,
author = {Andisheh Keykhah and Ensan, F and Ebrahim Bagheri},
title = {Query Expansion Using Pseudo Relevance Feedback on Wikipedia},
booktitle = {In International Workshop on Query Understanding and Reformulation for Mobile and Web Search collocated with The 9th ACM International Conference on Web Search and Data Mining},
year = {2016},
location = {San fransisco, USA},
keywords = {Query Expansion Using Pseudo Relevance Feedback on Wikipedia},
}

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%0 Conference Proceedings
%T Query Expansion Using Pseudo Relevance Feedback on Wikipedia
%A Andisheh Keykhah
%A Ensan, F
%A Ebrahim Bagheri
%J In International Workshop on Query Understanding and Reformulation for Mobile and Web Search collocated with The 9th ACM International Conference on Web Search and Data Mining
%D 2016

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