Looking for Trouble

This paper presents a method for mining potential troubles or obstacles related to the use of a given object. Some example instances of this relation are medicine, side effect and amusement park, height restriction . Our acquisition method consists of three steps. First, we use an unsupervised method to collect training samples from Web documents. Second, a set of expressions generally referring to troubles is acquired by a supervised learning method. Finally, the acquired troubles are associated with objects so that each of the resulting pairs consists of an object and a trouble or obstacle in using that object. To show the effectiveness of our method we conducted experiments using a large collection of Japanese Web documents for acquisition. Experimental results show an 85.5% precision for the top 10,000 acquired troubles, and a 74% precision for the top 10% of over 60,000 acquired object-trouble pairs.

• Type: Conference
• Year: 2008
• Where: COLING
• Authors: Stijn De Saeger, Kentaro Torisawa, Jun'ichi Kazama
• Keywords: Acquisition Method, COLING 2008, Computational Linguistics, Mining Potential Troubles, Supervised Learning Method