%0 Conference Proceedings
%T Extracting Comparative Commonsense from the Web
%+ Key Laboratory of Intelligent Information Processing, Institute of Computing Technology [Beijing]
%+ Graduate University of Chinese [Beijing] (UCAS)
%A Cao, Yanan
%A Cao, Cungen
%A Zang, Liangjun
%A Wang, Shi
%A Wang, Dongsheng
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 6th IFIP TC 12 International Conference on Intelligent Information Processing (IIP)
%C Manchester, United Kingdom
%Y Zhongzhi Shi; Sunil Vadera; Agnar Aamodt; David Leake
%I Springer
%3 Intelligent Information Processing V
%V AICT-340
%P 154-162
%8 2010-10-13
%D 2010
%R 10.1007/978-3-642-16327-2_21
%Z Computer Science [cs]/Digital Libraries [cs.DL]Conference papers
%X Commonsense acquisition is one of the most important and challenging topics in Artificial Intelligence. Comparative commonsense, such as "In general, a man is stronger than a woman", denotes that one entity has a property or quality greater or less in extent than that of another. This paper presents an automatic method for acquiring comparative commonsense from the World Wide Web. We firstly extract potential comparative statements from related texts based on multiple lexico-syntactic patterns. Then, we assess the candidates using Web-scale statistical features. To evaluate this approach, we use three measures: coverage of the web corpora, precision and recall which achieved 79.2%, 76.4% and 83.3%, respectively in our experiments. And the experimental results show that this approach profits significantly when the semantic similarity relationships are involved in the commonsense assessment.
%G English
%2 https://inria.hal.science/hal-01060361/document
%2 https://inria.hal.science/hal-01060361/file/CaoCZWW10.pdf
%L hal-01060361
%U https://inria.hal.science/hal-01060361
%~ IFIP
%~ IFIP-AICT
%~ IFIP-AICT-340
%~ IFIP-TC
%~ IFIP-TC12
%~ IFIP-IIP