%0 Report %1 vuw-CS-TR-06-6 %A Zhang, Mengjie %A Gao, Xiaoying %A Cao, Minh Duc %C New Zealand %D 2006 %K Baysian Citation Classification, Document Links Networks, algorithms, genetic programming, %N CS-TR-06-6 %T Experiments on Brood Size in GP with Brood Recombination Crossover for Object Recognition %U http://www.mcs.vuw.ac.nz/comp/Publications/CS-TR-06-6.abs.html %X citation links to improve the scientific paper classification performance. In this approach, we develop two refinement functions, a linear label refinement (LLR) and a probabilistic label refinement (PLR), to model the citation link structures of the scientific papers for refining the class labels of the documents obtained by the content-based Naive Bayes classification method. The approach with the two new refinement models is examined and compared with the content-based Naive Bayes method on a standard paper classification data set with increasing training set sizes. The results suggest that both refinement models can significantly improve the system performance over the content-based method for all the training set sizes and that PLR is better than LLR when the training examples are sufficient.

@techreport{vuw-CS-TR-06-6, abstract = {citation links to improve the scientific paper classification performance. In this approach, we develop two refinement functions, a linear label refinement (LLR) and a probabilistic label refinement (PLR), to model the citation link structures of the scientific papers for refining the class labels of the documents obtained by the content-based Naive Bayes classification method. The approach with the two new refinement models is examined and compared with the content-based Naive Bayes method on a standard paper classification data set with increasing training set sizes. The results suggest that both refinement models can significantly improve the system performance over the content-based method for all the training set sizes and that PLR is better than LLR when the training examples are sufficient.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {New Zealand}, author = {Zhang, Mengjie and Gao, Xiaoying and Cao, Minh Duc}, biburl = {https://www.bibsonomy.org/bibtex/2c29743e42d27669e1e5d005706618c16/brazovayeye}, institution = {Computer Science, Victoria University of Wellington}, interhash = {96a432ff92db0712c7b51efbbc77eb7c}, intrahash = {c29743e42d27669e1e5d005706618c16}, keywords = {Baysian Citation Classification, Document Links Networks, algorithms, genetic programming,}, number = {CS-TR-06-6}, timestamp = {2008-06-19T17:55:37.000+0200}, title = {Experiments on Brood Size in {GP} with Brood Recombination Crossover for Object Recognition}, url = {http://www.mcs.vuw.ac.nz/comp/Publications/CS-TR-06-6.abs.html}, year = 2006 }