期刊
JOURNAL OF BIOMEDICAL INFORMATICS
卷 44, 期 6, 页码 1086-1092出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jbi.2011.08.011
关键词
Interaction extraction; Hash; Graph kernel; Biomedical literature
资金
- Natural Science Foundation of China [60673039, 61070098]
- National High Tech Research and Development Plan of China [2006AA01Z151]
- Doctoral Program Foundation of Institutions of Higher Education of China [DUT10JS09]
- Liaoning Province Doctor Startup Fund [20091015]
Automated extraction of protein-protein interactions (PPIs) from biomedical literatures is an important topic of biomedical text mining. In this paper, we propose an approach based on neighborhood hash graph kernel for this task. In contrast to the existing graph kernel-based approaches for PPI extraction, the proposed approach not only has the capability to make use of full dependency graphs to represent the sentence structure but also effectively control the computational complexity. We evaluate the proposed approach on five publicly available PPI corpora and perform detailed comparisons with other approaches. The experimental result shows that our approach is comparable to the state-of-the-art PPI extraction system and much faster than all-path graph kernel approach on all five PPI corpora. (C) 2011 Elsevier Inc. All rights reserved.
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