This paper explores the use of innovative kernels based on syntactic and semantic structures for a target relation extraction task. Syntax is derived from constituent and dependen...
Truc-Vien T. Nguyen, Alessandro Moschitti, Giusepp...
This paper proposes a convolution forest kernel to effectively explore rich structured features embedded in a packed parse forest. As opposed to the convolution tree kernel, the p...
Extracting semantic relationships between entities from text documents is challenging in information extraction and important for deep information processing and management. This ...
This paper proposes a novel composite kernel for relation extraction. The composite kernel consists of two individual kernels: an entity kernel that allows for entity-related feat...
General graph matching methods often suffer from the lack of mathematical structure in the space of graphs. Using kernel functions to evaluate structural graph similarity allows u...