This paper presents an application of Boosting for classifying labeled graphs, general structures for modeling a number of real-world data, such as chemical compounds, natural lan...
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 the “Hierarchical Directed Acyclic Graph (HDAG) Kernel” for structured natural language data. The HDAG Kernel directly accepts several levels of both chunk...
Jun Suzuki, Tsutomu Hirao, Yutaka Sasaki, Eisaku M...
This paper proposes a tree kernel with contextsensitive structured parse tree information for relation extraction. It resolves two critical problems in previous tree kernels for r...
Guodong Zhou, Min Zhang, Dong-Hong Ji, Qiaoming Zh...
In recent years tree kernels have been proposed for the automatic learning of natural language applications. Unfortunately, they show (a) an inherent super linear complexity and (...