%A Yu Yan,Zhao Naixuan %T Weighted Topic Model for Patent Text Analysis %0 Journal Article %D 2018 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.2096-3467.2017.1068 %P 81-89 %V 2 %N 4 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_4499.shtml} %8 2018-04-25 %X

[Objective] This study aims to address the issues facing the topic model of patent text analysis such as the inclining to high frequency words and low discrimination rates. [Methods] First, we proposed a word weighting method for the traditional topic model. Then, the modified model assigned different weights to the words, and changed the probability of generating new words. [Results] Compared with traditional methods, the weighted patent topic model could identify the subjects more effectively. [Limitations] The weighting algorithm needs to be validated and optimized with more datasets. [Conclusions] The proposed model could effectively analyze the patent texts.