Download Advanced Data Mining and Applications: 9th International by Lishan Cui, Xiuzhen Zhang, Yan Wang, Lifang Wu (auth.), PDF

By Lishan Cui, Xiuzhen Zhang, Yan Wang, Lifang Wu (auth.), Hiroshi Motoda, Zhaohui Wu, Longbing Cao, Osmar Zaiane, Min Yao, Wei Wang (eds.)

ISBN-10: 3642539130

ISBN-13: 9783642539138

ISBN-10: 3642539149

ISBN-13: 9783642539145

The two-volume set LNAI 8346 and 8347 constitutes the completely refereed lawsuits of the ninth foreign convention on complicated facts Mining and purposes, ADMA 2013, held in Hangzhou, China, in December 2013.
The 32 average papers and sixty four brief papers offered in those volumes have been conscientiously reviewed and chosen from 222 submissions. The papers incorporated in those volumes hide the next issues: opinion mining, habit mining, info move mining, sequential info mining, net mining, snapshot mining, textual content mining, social community mining, category, clustering, organization rule mining, development mining, regression, predication, function extraction, id, privateness upkeep, purposes, and computing device learning.

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Additional info for Advanced Data Mining and Applications: 9th International Conference, ADMA 2013, Hangzhou, China, December 14-16, 2013, Proceedings, Part I

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1 H. Song, B. Yang, and X. Liu Pattern Matching Method Analysis We proposed a probability method in our former work [14]. Firstly we split the reviews in the source data set to sentences by punctuations and get word segmentation and part-of-speech (POS) tags for each. Then the typical sequential POS which called POS-patterns are extracted. We calculate the probability for each pattern identifying a subjective sentence and choose some effective patterns to create the pattern set. With the probability for each pattern, the rules for pattern matching are designed.

Though the gradient descent training doesn’t convergence quickly, it reduces over-fitting dramatically. After training, we obtain a classification function . For each inputting X derived from sentence s, it outputs a value y between 0 and 1. The effective sentence is recognized with the following formula ECS ULS where 5 (10) is a threshold set manually. Experiment We develop our approach according to an actual demanding. A dealer of cosmetics wants to mine the customer reviews to survey the popularity of a product.

In: Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC 2010). European Language Resources Association, ELRA (2010) 9. : Topic-based sentiment analysis for the social web: The role of mood and issue-related words. Journal of the American Society for Information Science and Technology 64(8), 1608–1617 (2013) 10. : Retrieval and creation of domain specific lexicon from noisy text data. In: Proceedings of ASCNT-2011, CDAC, Noida, Indiaz (2011) 11. : Learning domain-specific polarity lexicons.

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Advanced Data Mining and Applications: 9th International Conference, ADMA 2013, Hangzhou, China, December 14-16, 2013, Proceedings, Part I by Lishan Cui, Xiuzhen Zhang, Yan Wang, Lifang Wu (auth.), Hiroshi Motoda, Zhaohui Wu, Longbing Cao, Osmar Zaiane, Min Yao, Wei Wang (eds.)


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