Please use this identifier to cite or link to this item:
|Title:||A kernel-based feature weighting for text classification|
|Source:||Wittek, P.,Tan, C.L. (2009). A kernel-based feature weighting for text classification. Proceedings of the International Joint Conference on Neural Networks : 3373-3379. ScholarBank@NUS Repository. https://doi.org/10.1109/IJCNN.2009.5179022|
|Abstract:||Text classification by support vector machines can benefit from semantic smoothing kernels that regard semantic relations among index terms while computing similarity. Adding expansion terms to the vector representation can also improve effectiveness. However, existing semantic smoothing kernels do not employ term expansion. This paper proposes a new nonlinear kernel for text classification to exploit semantic relations between terms to add weighted expansion terms. © 2009 IEEE.|
|Source Title:||Proceedings of the International Joint Conference on Neural Networks|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 5, 2017
checked on Dec 9, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.