TY - GEN
T1 - GE-CKO
T2 - Proceedings - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004
AU - Sun, Jian-Tao
AU - Zhang, Ben-Yu
AU - Chen, Zheng
AU - Lu, Yu-Chang
AU - Shi, Chun-Yi
AU - Ma, Wei-Ying
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2004
Y1 - 2004
N2 - Most of current researches on Web page classification focus on leveraging heterogeneous features such as plain text, hyperlinks and anchor texts in an effective and efficient way. Composite kernel method is one topic of interest among them. It first selects a bunch of initial kernels, each of which is determined separately by a certain type of features. Then a classifier is trained based on a linear combination of these kernels. In this paper, we propose an effective way to optimize the linear combination of kernels. We proved that this problem is equivalent to solving a generalized eigenvalue problem. And the weight vector of the kernels is the eigenvector associated with the largest eigen-value. A support vector machine (SVM) classifier is then trained based on this optimized combination of kernels. Our experiment on the WebKB dataset has shown the effectiveness of our proposed method. © 2004 IEEE.
AB - Most of current researches on Web page classification focus on leveraging heterogeneous features such as plain text, hyperlinks and anchor texts in an effective and efficient way. Composite kernel method is one topic of interest among them. It first selects a bunch of initial kernels, each of which is determined separately by a certain type of features. Then a classifier is trained based on a linear combination of these kernels. In this paper, we propose an effective way to optimize the linear combination of kernels. We proved that this problem is equivalent to solving a generalized eigenvalue problem. And the weight vector of the kernels is the eigenvector associated with the largest eigen-value. A support vector machine (SVM) classifier is then trained based on this optimized combination of kernels. Our experiment on the WebKB dataset has shown the effectiveness of our proposed method. © 2004 IEEE.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-15544382266&origin=recordpage
U2 - 10.1109/wi.2004.10029
DO - 10.1109/wi.2004.10029
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 0769521002
T3 - Proceedings - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004
SP - 299
EP - 305
BT - Proceedings - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004
Y2 - 20 September 2004 through 24 September 2004
ER -