Chinese Data Feature Extraction Optimization in Data Detection
Author(s) -
Yun Zhang,
Zongze Jin,
Weimin Mu,
Weiping Wang
Publication year - 2017
Publication title -
destech transactions on engineering and technology research
Language(s) - English
Resource type - Journals
ISSN - 2475-885X
DOI - 10.12783/dtetr/oect2017/16126
Subject(s) - microblogging , computer science , social media , spectrum analyzer , computation , recall rate , similarity (geometry) , segmentation , data mining , precision and recall , feature extraction , the internet , feature (linguistics) , optimization algorithm , artificial intelligence , pattern recognition (psychology) , algorithm , mathematics , mathematical optimization , world wide web , image (mathematics) , telecommunications , philosophy , linguistics
While microblog is developing rapidly in China, microblog messages are also flooded with a large amount of repetitive information. Simhash algorithm has better precision and efficiency in the existing algorithms of similarity computation. In this paper, according to the actual scene of microblog, the deep optimization of traditional simhash is proposed through the segmentation optimization algorithm (Combined-Analyzer) and weight optimization algorithm (FFBOT-FID). To a certain extent, Combined-Analyzer solved the problem which real scene existed the massive internet words in microblog’s short text and FFBOT-FID helped us solve the problem of calculating weight which was caused by short text and timeliness. The experimental results use in microblog de-duplication and show that the optimization has a higher precision and recall rate than the traditional segmentation algorithm.
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