A Method on Chinese Thesauri

被引：0

作者：

Chen, Fu ^{[1
]}

Liu, Xi ^{[1
]}

Xu, Yuemei ^{[1
]}

Xu, Miaohua ^{[2
]}

Shi, Guangjun ^{[3
]}

机构：

[1] Beijing Foreign Studies Univ, Dept Comp Sci & Technol, Beijing, Peoples R China

[2] Hebei Surveying & Mapping Inst, Hebei, Peoples R China

[3] Chinese Acad Sci, Comp Network Informat Ctr, Beijing, Peoples R China

来源：

COLLABORATE COMPUTING: NETWORKING, APPLICATIONS AND WORKSHARING, COLLABORATECOM 2016 | 2017年 / 201卷

基金：

美国国家科学基金会;

关键词：

Chinese thesauri; Text analysis; Semantic distance;

D O I：

10.1007/978-3-319-59288-6_60

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In recent years, text analysis has become increasingly heated in many fields. And now, majority methods of text analysis are using Word2vec, Naive Bayes or so on to classify the large number of texts. But for the text itself, not all samples are useful for some high-requirement researches and only use one keywords to get the related sample is definitely not enough. In this paper, we provide a novel model of second text filtering with Chinese Thesauri. It includes roughly 5 steps: sample collecting, thesauri establishment, word-segment algorithm, word-frequency statistics and the calculation of text relevance. Its main purpose is making the sample texts more accurate with the keywords which are input by the user and avoiding the needless time and space waste.

引用

页码：601 / 608

页数：8

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