A three-phase method for patent classification

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题名:	A three-phase method for patent classification
作者:	陳彥良;Chen, Yen-Liang;Chang, Yuan-Che
贡献者:	管理學院資訊管理學系
关键词:	Accuracy;Algorithms;Approximation;Automatic classification;Classification;Data processing;Exact sciences and technology;Information and communication sciences;Information processing;Information processing and retrieval;Information retrieval systems. Information and document management system;Information retrieval. Man machine relationship;Information science. Documentation;Interprocessor communication;Inventors;IPC taxonomy;K nearest neighbors (KNN);K-means;Methods;Patent classification;Research process. Evaluation;Sciences and techniques of general use;Studies;Subgroups;Support vector machines (SVM);Three phase;Vector space model (VSM)
日期:	2012-11-01
上传时间:	2026-04-23 13:18:11 (UTC+8)
出版者:	Elsevier Ltd.;Kidlington: Elsevier Ltd
摘要:	摘要： ► So far no patent categorization method can classify patents down to the bottom level of IPC. ► This paper presents a novel categorization method named with the three phase categorization (TPC) algorithm. ► The TPC algorithm can classify patents down to the bottom level with a reasonable accuracy. ► The three phase approach provides a good framework to develop efficient patent classification algorithms for future research. An automatic patent categorization system would be invaluable to individual inventors and patent attorneys, saving them time and effort by quickly identifying conflicts with existing patents. In recent years, it has become more and more common to classify all patent documents using the International Patent Classification (IPC), a complex hierarchical classification system comprised of eight sections, 128 classes, 648 subclasses, about 7200 main groups, and approximately 72,000 subgroups. So far, however, no patent categorization method has been developed that can classify patents down to the subgroup level (the bottom level of the IPC). Therefore, this paper presents a novel categorization method, the three phase categorization (TPC) algorithm, which classifies patents down to the subgroup level with reasonable accuracy. The experimental results for the TPC algorithm, using the WIPO-alpha collection, indicate that our classification method can achieve 36.07% accuracy at the subgroup level. This is approximately a 25,764-fold improvement over a random guess. 出版者： Kidlington: Elsevier Ltd 出版日期： 2012-11-01 出處： Information Processing & Management, 2012-11, Vol.48 (6), p.1017-1030 資源來源： ScienceDirect 版權： 2011 Elsevier Ltd 版權： 2015 INIST-CNRS 版權： Copyright Pergamon Press Inc. Nov 2012 識別號： ISSN: 0306-4573 識別號： EISSN: 1873-5371 識別號： DOI: 10.1016/j.ipm.2011.11.001 識別號： CODEN: IPMADK
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