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2018 | OriginalPaper | Chapter

A Method for Topic Classification of Web Pages Using LDA-SVM Model

Authors : Yuliang Wei, Wei Wang, Bailing Wang, Bo Yang, Yang Liu

Published in: Proceedings of 2017 Chinese Intelligent Automation Conference

Publisher: Springer Singapore

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Abstract

The fast developments on the computer and networking technologies have made the Internet become the largest medium of information in the word at present. Many companies hope to be able to timely and effective access to information from the Internet. Efficient webpages classification system is needed. According to the classification requirements, we use LDA-SVM model for elaborate web category classification. And we discuss the impact of topic number K in LDA to the classification. The experiments show our method is efficient.

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Metadata
Title
A Method for Topic Classification of Web Pages Using LDA-SVM Model
Authors
Yuliang Wei
Wei Wang
Bailing Wang
Bo Yang
Yang Liu
Copyright Year
2018
Publisher
Springer Singapore
Book
Proceedings of 2017 Chinese Intelligent Automation Conference

Print ISBN: 978-981-10-6444-9

Electronic ISBN: 978-981-10-6445-6

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-6445-6_64