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Titlebook: Web Information Systems and Mining; International Confer Zhiguo Gong,Xiangfeng Luo,Fu Lee Wang Conference proceedings 2011 Springer-Verlag

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Redundant Feature Elimination by Using Approximate Markov Blanket Based on Discriminative Contributiperformance of classifiers. There are previous works to handle this problem by using pair-wise feature similarities, which do not consider discriminative contribution of each feature by utilizing the label information. Here we define an Approximate Markov Blanket (AMB) based on the metric of DIScrim
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Redundant Feature Elimination by Using Approximate Markov Blanket Based on Discriminative Contributiperformance of classifiers. There are previous works to handle this problem by using pair-wise feature similarities, which do not consider discriminative contribution of each feature by utilizing the label information. Here we define an Approximate Markov Blanket (AMB) based on the metric of DIScrim
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Text Clustering Based on LSA-HGSOMr space model (VSM) of term weight by using the theory of LSA, then semantic relation is included in the vector space model. Both theory analysis and experimental results confirm that LSA-HGSOM method decreases the number of vector, and enhances the efficiency and precision of text clustering.
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Text Clustering Based on LSA-HGSOMr space model (VSM) of term weight by using the theory of LSA, then semantic relation is included in the vector space model. Both theory analysis and experimental results confirm that LSA-HGSOM method decreases the number of vector, and enhances the efficiency and precision of text clustering.
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An Indent Shape Based Approach for Web Lists Mining the documents can be recognized, from which the lists of the target Web page can be extracted. Extensive experiments show that our approach achieves better performance and efficiency compared with existing approaches.
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An Indent Shape Based Approach for Web Lists Mining the documents can be recognized, from which the lists of the target Web page can be extracted. Extensive experiments show that our approach achieves better performance and efficiency compared with existing approaches.
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