New PDF release: Advanced Research in Applied Artificial Intelligence: 25th

By Qing He, Ye Duan, Danyang Zhang (auth.), He Jiang, Wei Ding, Moonis Ali, Xindong Wu (eds.)

ISBN-10: 3642310869

ISBN-13: 9783642310867

ISBN-10: 3642310877

ISBN-13: 9783642310874

This quantity constitutes the completely refereed convention court cases of the twenty fifth foreign convention on business Engineering and different purposes of utilized Intelligend structures, IEA/AIE 2012, held in Dalian, China, in June 2012. the complete of eighty two papers chosen for the lawsuits have been rigorously reviewed and chosen from a number of submissions. The papers are equipped in topical sections on computing device studying equipment; cyber-physical process for clever transportation functions; AI purposes; evolutionary algorithms, combinatorial optimization; modeling and aid of cognitive and affective human methods; traditional language processing and its purposes; social community and its functions; mission-critical functions and case stories of clever platforms; AI equipment; sentiment research for asian languages; elements on cognitive computing and clever interplay; spatio-temporal datamining, established studying and their purposes; choice making and data dependent platforms; development attractiveness; agent dependent platforms; choice making ideas and cutting edge wisdom administration; laptop studying applications.

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Read or Download Advanced Research in Applied Artificial Intelligence: 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012, Dalian, China, June 9-12, 2012. Proceedings PDF

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Additional info for Advanced Research in Applied Artificial Intelligence: 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012, Dalian, China, June 9-12, 2012. Proceedings

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The concept of Named Object (NO) is introduced in [7] as part of a web page that can be named in a user-understandable way. Product data with a name, price and image is given as an example domain dependent NO. g. ) and using web design patterns. Naïve Bayes is a widely used classification method for text categorization based on word occurrences in documents [8][9]. In this method, Bayes’ rule is used for estimating the probability of a document d to be classified in category c, where d is composed of k words, w1, w2, …wk.

So, it is expensive to set parameters until we find the best parameters for training datasets. Grouping co-occurrence filtering method does not need setting the parameter, instead it can detect harmful documents by smoothing noise of co-occurrences without setting parameters. We can reduce the work to create filtering because the filter removes the process of setting parameters. So, by using the Grouping Co-occurrence filtering, we can detect harmful or safe documents at low cost. Meanwhile, accuracy of each filtering must be verified because it is unclear whether grouping co-occurrence filtering works as filtering.

Yoshimura, Y. Fujii, and T. Ito Table 2. 883 Conclusion We gathered datasets to implement the two Filtering, and implemented the Grouping filtering and Co-occurrence filtering. Since two filtering differ to deal with noisy co-occurrence, we verify each feature and accuracy as a filtering method. Our experimental results found that grouping co-occurrence filtering has higher accuracy than Gray Robinson filtering. Grouping filtering does not dispose of all noise; it smoothes noise. Grouping filtering can get several feature values and expresses more ambiguity and detecte harmful or safe documents without setting parameters.

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Advanced Research in Applied Artificial Intelligence: 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012, Dalian, China, June 9-12, 2012. Proceedings by Qing He, Ye Duan, Danyang Zhang (auth.), He Jiang, Wei Ding, Moonis Ali, Xindong Wu (eds.)


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