Abstract
Focused on the problem of numerous labeling works on the expert homepage in the procedure of Chinese expert entity homepage recognition, in this paper, a method of Chinese expert entity homepage recognition based on the Co-EM proposed. In detail, firstly, collect the names of Chinese expert entity and the corresponding web pages, and then label a small quantity of web pages. Secondly for Chinese entity characteristics, extract the hyperlink features and the web page content features as two independent feature sets. Thirdly train the hyperlink classifier using the hyperlink feature set and label the all the expert entity homepages, and then train the content classifier using the web page content feature set and the labels which were labeled by the hyperlink classifier. Use the labels which were labeled by the content classifier to update the hyperlink classifier. Repeat the procedure until the two classifiers converge. Finally, experiments were done by employing the method of 10-fold cross validation. The results show that the method based on the Co-EM semi-supervised algorithm can uses the unlabeled web pages effectively and there is an increase of accuracy of recognition compared with using the labeled web pages only.
This paper is supported by National Nature Science Foundation (60863011), Yunnan Nature Science Foundation (2008CC023), Yunnan Young and Middle-Aged Science and Technology Leaders Foundation (2007PY01-11).
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Liu, L., Yu, Z., Li, L. (2011). Chinese Expert Entity Homepage Recognition Based on Co-EM. In: Gong, Z., Luo, X., Chen, J., Lei, J., Wang, F.L. (eds) Web Information Systems and Mining. WISM 2011. Lecture Notes in Computer Science, vol 6988. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23982-3_22
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