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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (4): 81-89    DOI: 10.11925/infotech.2096-3467.2017.1068
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Weighted Topic Model for Patent Text Analysis
Yan Yu1,2(),Naixuan Zhao1
1Information Service Department, Nanjing Tech University, Nanjing 210009, China
2Computer Science Department, Southeast University Chengxian College, Nanjing 211816, China
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[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.

Key wordsText Analysis      Patent      Weighted Topic Model     
Received: 26 October 2017      Published: 11 May 2018

Cite this article:

Yan Yu,Naixuan Zhao. Weighted Topic Model for Patent Text Analysis. Data Analysis and Knowledge Discovery, 2018, 2(4): 81-89.

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