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Clustering patent document in the field of ICT (Information Communication Technology)

机译:ICT(信息和通信技术)领域的专利文件的聚类

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摘要

The current classification of patent data that refers to the IPC (International Patent Classification) of the WIPO (World Intellectual Property Organization), deemed not reflect the classification of the field of ICT (Information & Communication Technology). ICT applications are usually included in sections G (Physics) and H (Electricity). This paper will evaluate the eight groupings of patents based on the IPC classes (G01, G06, G09, G11, H01, H03, H04, and H06) of patents registered in the Directorate General of Intellectual Property Rights in Indonesia, from the year 1991 to 2000. The algorithm used to grouping is KMeans, KMeans++, Hierchical Clustering, and a combination of these three algorithms with SVD (Singular Value Decomposition). For external validation, Purity and F-Measure are used, whereas Silhouette is used for internal validation. From the experimental results it can be concluded that SVD provides improvements to the clustering results. In addition, the use of abstract does not necessarily improve the performance of clustering, and the use of phrase does not always yield better cluster than the use of the word as index. Moreover, no cluster has purity measure greater than 50%, which means that the existing IPC classification has not been able to accommodate the field of ICT appropriately.
机译:当前的专利数据分类是指WIPO(世界知识产权组织)的IPC(国际专利分类),被认为不反映ICT(信息和通信技术)领域的分类。 ICT应用通常包含在G(物理)和H(电)部分中。本文将从1991年开始,根据在印度尼西亚知识产权总局注册的IPC类专利(G01,G06,G09,G11,H01,H03,H04和H06)评估八类专利。到2000年。用于分组的算法是KMeans,KMeans ++,Hierchical Clustering,以及这三种算法与SVD(奇异值分解)的组合。对于外部验证,使用“纯度”和“ F量度”,而对“内部验证”使用“剪影”。从实验结果可以得出结论,SVD改善了聚类结果。此外,抽象的使用并不一定会改善聚类的性能,短语的使用并不一定总比词作为索引的使用产生更好的聚类。此外,没有一个集群的纯度度量值大于50%,这意味着现有的IPC分类不能适当地适应ICT领域。

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