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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Project supported by the National Natural Science of China undergrant No. 61371177.
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Wei, Y., Wang, W., Wang, B., Yang, B., Liu, Y. (2018). A Method for Topic Classification of Web Pages Using LDA-SVM Model. In: Deng, Z. (eds) Proceedings of 2017 Chinese Intelligent Automation Conference. CIAC 2017. Lecture Notes in Electrical Engineering, vol 458. Springer, Singapore. https://doi.org/10.1007/978-981-10-6445-6_64
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DOI: https://doi.org/10.1007/978-981-10-6445-6_64
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