Download Advanced Research on Computer Science and Information by Xiang Xu, Kun Zou (auth.), Gang Shen, Xiong Huang (eds.) PDF

By Xiang Xu, Kun Zou (auth.), Gang Shen, Xiong Huang (eds.)

ISBN-10: 364221410X

ISBN-13: 9783642214103

This two-volume set (CCIS 152 and CCIS 153) constitutes the refereed lawsuits of the foreign convention on machine technological know-how and knowledge Engineering, CSIE 2011, held in Zhengzhou, China, in may perhaps 2011. The 159 revised complete papers provided in either volumes have been rigorously reviewed and chosen from a good number of submissions. The papers current unique learn effects which are generally appropriate to the idea and purposes of computing device technological know-how and knowledge Engineering and tackle a wide selection of subject matters comparable to algorithms, automation, man made intelligence, bioinformatics, machine networks, laptop safeguard, computing device imaginative and prescient, modeling and simulation, databases, info mining, e-learning, e-commerce, e-business, picture processing, wisdom administration, multimedia, cellular computing, common computing, open and leading edge schooling, development popularity, parallel computing, robotics, instant networks, and net applications.

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Extra info for Advanced Research on Computer Science and Information Engineering: International Conference, CSIE 2011, Zhengzhou, China, May 21-22, 2011, Proceedings, Part II

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Morgan Kaufmann, San Francisco (2000) 2. : Transductive LSI for short text classification problems. In: Proceedings of the 17th International Florida Artificial Intelligence Research Society Conference. AAAI Press, Florida (2004) 3. : Transductive learning for short text classificaton problems using latent semantic indexing. International Journal of Pattern Recognition and Artificial Intelligence 19(2), 143–151 (2005) 4. : Method for Chinese short text classification based on feature extension.

1 to extract the agent and patient relation, the number and the coverage of the relations are limited. That is because of the HowNet’s coverage and its language’s characteristic. Fig. 2. Model 1 to 4 Sememes exist in the signature-file as a structure of tree. The trees do not only reflect the hyponymic relation but also mark the common features in []. The common features are the properties of a class of concepts which use this sememe as the first sememe. Moreover, the lower sememe could succeed its higher sememe’s agentfeature or patient-feature.

3)Use the information provided by HowNet and the method of this paper to make sure whether the concept pairs have agent or patient relation. (4)According to actual needs, calculate the strength of relation and filter the wordpairs which do not meet our requirements. Step (3) is the most important step of this model. 2 of this section. 1 HowNet and a Conventional Method HowNet[9] use the concepts of Chinese or English words as described objects, in order to reflect the relation between different concepts.

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