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Author : Jean-Charles Lamirel, Shadi Al Shehabi, Martial Hoffmann, Claire Francois

Intelligent patent analysis through the use of a neural network experiment of multi-viewpoint analysis with the MultiSOM model. Author : Jean-Charles Lamirel, Shadi Al Shehabi, Martial Hoffmann, Claire Francois Reporter : Tze Ho-Lin 2006/8/23. Association for Computational Linguistics, 2006.

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Author : Jean-Charles Lamirel, Shadi Al Shehabi, Martial Hoffmann, Claire Francois

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  1. Intelligent patent analysis through the use of a neural network experiment of multi-viewpoint analysis with the MultiSOM model Author : Jean-Charles Lamirel, Shadi Al Shehabi, Martial Hoffmann, Claire Francois Reporter : Tze Ho-Lin 2006/8/23 Association for Computational Linguistics, 2006

  2. Outline • Motivation • Objectives • Method • Application • Evaluation • Conclusion • Personal Comments

  3. Motivation • Most of the classical information analysis tools can only manage an analysis of the studied domain in a global way. • In the domain of patent analysis, assisting a user in carrying out the complex process of analyzing large quantities of such information. V.S.

  4. Objectives • Demonstrates the efficiency of a viewpoint-oriented-analysis as compared to a global analysis in the domain of patents. V.S.

  5. (1) Method: Inter-Map Communication Mechanism [3] Transmitto other maps to which these data are associated [2] data nodes associated to the activated class nodes

  6. Method: Inter-Map Communication Mechanism (2) n : a node associated to a data jn : n associated cluster on the source map g : Cluster->Data Data->Cluster || i || : the number of data associated to the cluster i Vector Space Model (3) (4)

  7. Application • Final Index Sets • Patent Document Step 1 parse the structure of the patent abstracts to extract the subfields corresponding to the Use and to the Advantages viewpoints. Step 2 the rough index set of each subfield is constructed by the use of a basic computer-based indexing tool. Step 3 the normalization of the rough index set associated to each viewpoint is performed by the domain expert in order to obtain the final index sets.

  8. Application Table 1: Summary of the results of patent indexation and map building. GlobMin

  9. Evaluation (6) (5) (7) (9) (8) Recall Precision F-measure Table 2: Summary of the results of Quality, Recall and Precision evaluation

  10. Conclusion • Objective evaluation • For the domain experts: the original multiple viewpoints classification approach of MultiSOM tends to reduce the noise.

  11. Personal Comments • Applications • Theory, News … • Advantages • Reduce the noise • More tends to general analyst’s analysis way. • Disadvantage • Writing: Formula description is too rough. • Method: Doesn’t use large data set to experiment yet.

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