Dependency trigram model for social relation extraction from news articles

Authors:
Maengsik Choi;Harksoo Kim;Bruce W. Croft
Affiliations:
Kangwon National University, Chuncheon-si, South Korea;Kangwon National University, Chuncheon-si, South Korea;University of Massachusetts, Amherst, Amherst, MA, USA
Venue:
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Year:
2012

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Abstract

We propose a kernel-based model to automatically extract social relations such as economic relations and political relations between two people from news articles. To determine whether two people are structurally associated with each other, the proposed model uses an SVM (support vector machine) tree kernel based on trigrams of head-dependent relations between them. In the experiments with the automatic content extraction (ACE) corpus and a Korean news corpus, the proposed model outperformed the previous systems based on SVM tree kernels even though it used more shallow linguistic knowledge.