Constructing complex search tasks with coherent subtask search goals

Ting Xuan Wang, Wen Hsiang Lu

研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)


Nowadays, due to the explosive growth of web content and usage, users deal with their complex search tasks by web search engines. However, conventional search engines consider a search query corresponding only to a simple search task. In order to accomplish a complex search task, which consists of multiple subtask search goals, users usually have to issue a series of queries. For example, the complex search task "travel to Dubai" may involve several subtask search goals, including reserving hotel room, surveying Dubai landmarks, booking flights, and so forth. Therefore, a user can efficiently accomplish his or her complex search task if search engines can predict the complex search task with a variety of subtask search goals. In this work, we propose a complex search task model (CSTM) to deal with this problem. The CSTM first groups queries into complex search task clusters, and then generates subtask search goals from each complex search task cluster. To raise the performance of CSTM, we exploit four web resources including community question answering, query logs, search engine result pages, and clicked pages. Experimental results show that our CSTM is effective in identifying the comprehensive subtask search goals of a complex search task. 2015 Copyright is held by the owner/author(s).

期刊ACM Transactions on Asian and Low-Resource Language Information Processing
出版狀態Published - 2016 2月

All Science Journal Classification (ASJC) codes

  • 電腦科學(全部)


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