TITLE:
Protein-Protein Interaction Extraction Based on Convex Combination Kernel Function
AUTHORS:
Peng Chen, Jianyi Guo, Zhengtao Yu, Sichao Wei, Feng Zhou, Xin Yan
KEYWORDS:
Protein-Protein Interaction; Support Vector Machine; Convex Combination Kernel Function
JOURNAL NAME:
Journal of Computer and Communications,
Vol.1 No.5,
November
8,
2013
ABSTRACT: Owing to the effect of classified
models was different in Protein-Protein Interaction(PPI) extraction, which was made by
different single kernel functions, and only using single kernel function
hardly trained the optimal classified model to extract PPI, this paper presents
a strategy to find the optimal kernel function from a kernel function set. The
strategy is that in the kernel function set which consists of
different single kernel functions, endlessly finding the last two kernel
functions on the performance in PPI extraction, using their optimal kernel
function to replace them, until there is only one kernel function and it’s the
final optimal kernel function. Finally, extracting PPI using the classified
model made by this kernel function. This paper conducted the PPI extraction
experiment on AIMed corpus, the experimental result shows that the optimal convex
combination kernel function this paper presents can effectively improve the
extraction performance than single kernel function, and it gets the best
precision which reaches 65.0 among the similar PPI extraction systems.