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In this poster, we describe a novel session-based search engine, which puts the search in context. The search engine has a number of session-based features including expansion of the current query with user query history and clickthrough data (title and summary of clicked web pages) in the same search session and the session boundary recognition through temporal closeness and probabilistic similarity between query terms. In addition, the search engine visualizes the rank change of web pages as different queries are submitted in the same search session to help the user reformulate the query.
@inproceedings{1009086, author = {Smitha Sriram and Xuehua Shen and Chengxiang Zhai}, title = {A session-based search engine}, booktitle = {SIGIR '04: Proceedings of the 27th annual international conference on Research and development in information retrieval}, year = {2004}, isbn = {1-58113-881-4}, pages = {492--493}, location = {Sheffield, United Kingdom}, doi = {http://doi.acm.org/10.1145/1008992.1009086}, publisher = {ACM Press}, }  ©2005 Association for Computing Machinery |
