基于引文的DEA从专利文本数据中选择核心词

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI:10.1109/ICAIIC.2019.8668999

Shigeaki Onoda, K. Okuhara

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引用次数: 0

摘要

网络包含大量的数据，比如专利。本研究的目的在于发现专利文本数据的规律，建立新的模型。因此，我们提出了一种新的加权DEA方法来处理专利等非结构化数据。我们提出的方法是有利的，因为与TF-IDF和其他加权方法相比，它考虑了专利的价值。利用本文提出的方法，对专利领域的文本挖掘进行了探索。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Selection of Core Words from Textual Patent Data with DEA based on Citation

The web includes enormous data such as patents. The purpose of this research finds the rule of textual patent data and creates new model. Hence, we suggest new weighted method using DEA to handle unstructured data like patent. Our proposed method is advantageous because this considers the value of the patent compared with TF-IDF and other weighted methods. Using suggested method, we probe new text-mining in the field of patent.

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来源期刊

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

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