Modern models of relation extraction for tasks like ACE are based on supervised learning of relations from small hand-labeled corpora. We investigate an alternative paradigm that ...
Mike Mintz, Steven Bills, Rion Snow, Daniel Jurafs...
This paper discusses the problem of marrying structural similarity with semantic relatedness for Information Extraction from text. Aiming at accurate recognition of relations, we ...
Sophia Katrenko, Pieter W. Adriaans, Maarten van S...
Background: Automated extraction of protein-protein interactions (PPI) is an important and widely studied task in biomedical text mining. We propose a graph kernel based approach ...
This paper describes a novel approach to the semantic relation detection problem. Instead of relying only on the training instances for a new relation, we leverage the knowledge l...
Chang Wang, James Fan, Aditya Kalyanpur, David Gon...
This paper discusses local alignment kernels in the context of the relation extraction task. We define a local alignment kernel based on the Smith-Waterman measure as a sequence s...