TY - GEN
T1 - Research on tree kernel-based personal relation extraction
AU - Peng, Cheng
AU - Gu, Jinghang
AU - Qian, Longhua
PY - 2012
Y1 - 2012
N2 - In this paper, a kernel-based personal relation extraction method is presented. First, a personal relation corpus is built through filtering and expansion from the ACE2005 Chinese corpus. Then, the structured information, which is appropriate for personal relation extraction, is constructed by applying pruning rules on the basis of the shortest path-enclosed tree. After that,TongYiCi CiLin semantic information is embedded into the structured information. Finally, re-sampling techniques are employed to alleviate the data imbalance problem inherent in the corpus distribution. Experimental results show that, the pruning rules, the embedding of semantic information and the application of re-sampling techniques can improve the F1 score by 3.5, 3.0 and approximate 3.0 units respectively compared with the baseline system. It suggests that the method we propose is effective for personal relation extraction.
AB - In this paper, a kernel-based personal relation extraction method is presented. First, a personal relation corpus is built through filtering and expansion from the ACE2005 Chinese corpus. Then, the structured information, which is appropriate for personal relation extraction, is constructed by applying pruning rules on the basis of the shortest path-enclosed tree. After that,TongYiCi CiLin semantic information is embedded into the structured information. Finally, re-sampling techniques are employed to alleviate the data imbalance problem inherent in the corpus distribution. Experimental results show that, the pruning rules, the embedding of semantic information and the application of re-sampling techniques can improve the F1 score by 3.5, 3.0 and approximate 3.0 units respectively compared with the baseline system. It suggests that the method we propose is effective for personal relation extraction.
KW - personal relation extraction
KW - re-sampling
KW - social network
KW - tongyici cilin
KW - tree kernel
UR - http://www.scopus.com/inward/record.url?scp=84869208646&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-34456-5_21
DO - 10.1007/978-3-642-34456-5_21
M3 - Conference article published in proceeding or book
AN - SCOPUS:84869208646
SN - 9783642344558
T3 - Communications in Computer and Information Science
SP - 225
EP - 236
BT - Natural Language Processing and Chinese Computing - First CCF Conference, NLPCC 2012, Proceedings
T2 - 1st CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2012
Y2 - 31 October 2012 through 5 November 2012
ER -