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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

Intelligent Database Systems Lab

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I. M.Outline

Motivation Objective Methodology Experiments Conclusion Comments

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I. M.Motivation

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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.

Intelligent Database Systems Lab

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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.

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I. M.Methodology

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I. M.Methodology

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Phase 1: Collect patent documents

PatentDB

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I. M.Methodology

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Phase 2:Text preprocessing

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I. M.Methodology

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Phase 3: Generate category * term vectors

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Phase 4: Generate term * category vector

Phase 5: Generate document * category vectors

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I. M.Experiments

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I. M.Experiments

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I. M.Experiments

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I. M.Experiments

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I. M.Conclusion

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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.

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I. M.Comments

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Advantage IPC_based SVM better than previous methods.

Application Information Retrieval