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Intelligent Database Systems Lab N.Y.U.S.T. I. M. An IPC-based vector space model for patent retrieval Presenter: Jun-Yi Wu Authors: Yen-Liang Chen, Yu-Ting.

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1 Intelligent Database Systems Lab N.Y.U.S.T. I. M. An IPC-based vector space model for patent retrieval Presenter: Jun-Yi Wu Authors: Yen-Liang Chen, Yu-Ting Chiu 2011 IPM 國立雲林科技大學 National Yunlin University of Science and Technology

2 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Outline Motivation Objective Methodology Experiments Conclusion Comments 2

3 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Motivation 3 The weakness in traditional VSM is that the indexing vocabulary changes whenever changes occur in the document set, or the indexing vocabulary selection algorithms, or parameters of the algorithms, or if wording evolution occurs.

4 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Objective The major objective of this research is to design a method to solve the afore-mentioned problems for patent retrieval. The proposed method utilizes the special characteristics of the patent documents, the International Patent Classification (IPC) codes, to generate the indexing vocabulary for presenting all the patent documents. 4

5 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 5

6 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 6 Phase 1: Collect patent documents Patent DB

7 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 7 Phase 2:Text preprocessing

8 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 8 8 Phase 3: Generate category * term vectors

9 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 9 9

10 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology 10 Phase 4: Generate term * category vector Phase 5: Generate document * category vectors

11 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 11

12 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 12

13 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 13

14 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 14

15 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 15

16 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Conclusion 16 A novel method, IPC-based VSM, was proposed for generating vectors to represent patent documents. The indexing vocabulary generated in IPC-based VSM was better at finding similar documents than either of the traditional methods.

17 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Comments 17 Advantage  IPC_based SVM better than previous methods. Application  Information Retrieval


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