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ConSOM: A conceptional self-organizing map model for text clustering

ConSOM: A conceptional self-organizing map model for text clustering. Presenter : You Lin Chen Authors : Yuanchao Liua,b,, Xiaolong Wanga, Chong Wub. 2007.WI.7. Outline. Motivation Objective Methodology Experiments Conclusion Comments. Motivation. 單位： TF-IDF.

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ConSOM: A conceptional self-organizing map model for text clustering

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  1. ConSOM: A conceptional self-organizing map model for text clustering Presenter : You Lin Chen Authors : Yuanchao Liua,b,, Xiaolong Wanga, Chong Wub 2007.WI.7

  2. Outline • Motivation • Objective • Methodology • Experiments • Conclusion • Comments

  3. Motivation 單位：TF-IDF The similarity of two vectors is great, then in most situations it is because they share more words. Whereas if two documents share few words, thery usually will be assigned into different clusters.

  4. Objectives A novel conceptional self-organizing map model (ConSOM) is proposed for text clustering. InConSOM, all input documents and neurons are repre-sented by two vectors: one in traditional feature space and the other in extended concept space.

  5. Methodology

  6. Methodology

  7. Methodology

  8. Methodology

  9. Experiments

  10. Conclusion • In this way, the documents about same topic can be assigned into one cluster even though they share few words. • ConSOM are more sensitive to semantics and can achieve better performance than traditional ‘‘SOM plus VSM’’ mode.

  11. Comments • Advantage • … • Drawback • … • Application • …

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