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Method of Classification Mapping between IPC and CLC Based on Machine Learning

Author: JinXueRu
Tutor: QiJianDong
School: Beijing Forestry University
Course: Applied Computer Technology
Keywords: Category mapping International Patent Classification Chinese Library Classification Machine Learning
CLC: TP391.1
Type: Master's thesis
Year: 2011
Downloads: 24
Quote: 1
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Abstract


With the rapid development of modern science and technology , literature resources also increased dramatically , how to find out in the flood of information they are interested in the latest and the most comprehensive information has become an urgent problem . The patent can reflect the dynamic of the latest scientific research , development status of research topics , technical level and legal status information , and has great scientific value and commercial value . However , compared to other literature resources , patent information utilization Que Shibi lower . Today , more and more attention in the patent information to achieve interoperability of the patent and journal literature has important significance . IPC (International Patent Classification, IPC) is the most common international organizations and management tools of the patent literature . Chinese Library Classification (Chinese Library Classification, CLC) is the most widely used classification method , most of the literature in order to carry out the management and use . Between IPC and CLC mapping important way for cross browser and retrieve patent information and other literature interrelated and different organizational system . In this paper, the research on the basis of the existing interoperability projects and taxonomy category mapping method is proposed based on machine learning classification algorithm to achieve the the categories mapping method between IPC and CLC training corpus of a category of identification information this category classification , then use the classification to another classification categories identified corpus classification , analysis of the classification results to determine with which one or which category has a corresponding relationship . Finally through the experimental verification of the method can accomplish the mapping between the different categories .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Text Processing
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