By Dell Zhang, Karl Prior, Mark Levene, Robert Mao, Diederik van Liere (auth.), Shuigeng Zhou, Songmao Zhang, George Karypis (eds.)
This e-book constitutes the refereed complaints of the eighth overseas convention on complex information Mining and functions, ADMA 2012, held in Nanjing, China, in December 2012. The 32 normal papers and 32 brief papers awarded during this quantity have been rigorously reviewed and chosen from 168 submissions. they're equipped in topical sections named: social media mining; clustering; laptop studying: algorithms and functions; category; prediction, regression and popularity; optimization and approximation; mining time sequence and streaming information; net mining and semantic research; info mining functions; seek and retrieval; info suggestion and hiding; outlier detection; subject modeling; and knowledge dice computing.
Read Online or Download Advanced Data Mining and Applications: 8th International Conference, ADMA 2012, Nanjing, China, December 15-18, 2012. Proceedings PDF
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Extra info for Advanced Data Mining and Applications: 8th International Conference, ADMA 2012, Nanjing, China, December 15-18, 2012. Proceedings
Given a threshold , if DD(w) < α, we eliminate w from the learned lexicon because it does not show an obvious orientation to either of the sentiment categories. To evaluate the performance of the lexicon learning and the optimization methods, we propose a lexicon based sentiment analysis algorithm for Chinese microblog, which is given in Algorithm 1. In Algorithm 1, the number of matched positive and negative words from the lexicon is counted and the negation words are also considered during the classiﬁcation.
In: Proceedings of the 2nd International Workshop on Emerging Trends in Free/Libre/Open Source Software Research and Development (FLOSS), Vancouver, Canada, pp. 7–12 (2009) 9. : Life, death, and lawfulness on the electronic frontier. In: CHI, Atlanta, GA, USA, pp. 383–390 (1997) 10. : Detecting novel associations in large data sets. Science 334(6062), 1518–1524 (2011) 11. : The singularity is not near: Slowing growth of Wikipedia. edu Abstract. Probability models have been used in cross-modal multimedia information retrieval recently by building conjunctive models bridging the text and image components.
In this paper, we propose an unsupervised sentiment lexicon learning method based on the emoticons in the microblog data. Intuitively, our basic assumption is that positive words often appear in the microblog posts with positive emoticons, and vice versa. We design appropriate rules to eliminate spam data, and collect the puriﬁed training microblog dataset with emoticons. We develop an algorithm to pick out sentiment words based on their occurrence probability in each category of the training dataset, and the accuracy of the learned lexicon is further improved by using the whole microblog space as the training corpus.
Advanced Data Mining and Applications: 8th International Conference, ADMA 2012, Nanjing, China, December 15-18, 2012. Proceedings by Dell Zhang, Karl Prior, Mark Levene, Robert Mao, Diederik van Liere (auth.), Shuigeng Zhou, Songmao Zhang, George Karypis (eds.)