Affiliations: [a]
School of Foreign Studies of Yanshan University, Qinhuangdao, Hebei, P.R. China | [b]
School of Information Science and Engineering of Yanshan University, Qinhuangdao, Hebei, P.R. China | [c]
School of Acupuncture-moxisition and Tuina of Shanghai University of Traditional Chinese Medicine, Shanghai, P. R. China
Correspondence:
[*]
Corresponding author. Jianping Yu and Jilin Fu, School of Foreign Studies of Yanshan University, 066004, Qinhuangdao, Hebei, P.R. China. E-mails: [email protected] (Jianping Yu) and [email protected] (Jilin Fu).
Abstract: The development of natural language processing promotes the progress of general linguistic studies. Based on the selected features and the extracted rules for word sense disambiguation (WSD), some valuable knowledge of the relations between linguistic features and word sense classes may be discovered, which may provide theoretical and practical evidence and references for lexical semantic study and natural language processing. However, many available approaches of feature selection for WSD are in the end to end operation, they can only select the optimal features for WSD, but not provide the rules for WSD, which makes knowledge discovery impossible. Therefore, a new Filter-Attribute partial ordered structure diagram (Filter-APOSD) approach is proposed in this article to fulfill both feature selection and knowledge discovery. The new approach is a combination of a Filter approach and an Attribute Partial Ordered Structure Diagram (APOSD) approach. The Filter approach is designed and used for filtering the simplest rules for WSD, and the APOSD approach is used to provide the complementary rules for WSD and visualize the structure of the datasets for knowledge discovery. The features occurring in the final rule set are selected as the optimal features. The proposed approach is verified by the benchmark data set from the SemEval-2007 preposition sense disambiguation corpus with around as the target word for WSD. The test result shows that the accuracy of WSD of around is greatly improved comparing with the one by the state of the art, and 17 out of 22 features are finally selected and ranked according to their contribution to the WSD, and some knowledge on the relations between the word senses and the selected features is discovered.
Keywords: Filter-APOSD approach, feature selection, word sense disambiguation, knowledge discovery, English preposition
