Proceedings:
Book One
Volume
Issue:
Proceedings of the AAAI Conference on Artificial Intelligence, 21
Track:
Special Track on Artificial Intelligence and the Web
Downloads:
Abstract:
This paper studies a text mining problem, comparative sentence mining (CSM). A comparative sentence expresses an ordering relation between two sets of entities with respect to some common features. For example, the comparative sentence “Canon’s optics are better than those of Sony and Nikon” expresses the comparative relation: (better, [optics], [Canon], [Sony, Nikon]). Given a set of evaluative texts on the Web, e.g., reviews, forum postings, and news articles, the task of comparative sentence mining is (1) to identify comparative sentences from the texts and (2) to extract comparative relations from the identified comparative sentences. This problem has many applications. For example, a product manufacturer wants to know customer opinions of its products in comparison with those of its competitors. In this paper, we propose two novel techniques based on two new types of sequential rules to perform the tasks. Experimental evaluation has been conducted using different types of evaluative texts from the Web. Results show that our techniques are very promising.
AAAI
Proceedings of the AAAI Conference on Artificial Intelligence, 21