Using Convex Combination Kernel Function to Extract Entity Relation in Specific Field

Abstract

Kernel method has been proven to be effective in measuring the similarity of two complex relation patterns. Aim at the optimization problem of compound kernel functions, this paper presents a method of finding the optimal convex combination kernel function, which is comprised of multiple kernel functions and needs to be optimized. After preprocessing the corpus and selecting features including lexical information, phrases syntax information and dependency information, the feature matrix was constructed by using these features. The optimal kernel function can be found in the process of mapping the feature matrix to different high-dimensional matrix, and the different classification models can be obtained. The experiments are conducted on the domain dataset from Web and the experimental results show that our approach outperforms state-of-the-art learning models such as ME or Convolution tree kernel.