Paper: Textual Demand Analysis: Detection of Users% Wants and Needs from Opinions

ACL ID C08-1052
Title Textual Demand Analysis: Detection of Users% Wants and Needs from Opinions
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2008
Authors

This paper tackles textual demand analy- sis, the task of capturing what people want or need, rather than identifying what they like or dislike, on which much conven- tional work has focused. It exploits syn- tactic patterns as clues to detect previously unknown demands, and requires domain- dependent knowledge to get high recall. To build such patterns we created an unsuper- vised pattern induction method relying on the hypothesis that there are commonly de- sired aspects throughout a domain corpus. Experimental results show that the pro- posed method detects twice to four times as many demand expressions in Japanese discussion forums compared to a baseline method.