Anaphora resolution in Chinese texts based on domain ontology

被引:0
作者
Shi, Shumin [1 ]
Huang, Heyan [1 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Comp Sci & Technol, Nanjing 210094, Peoples R China
来源
RECENT ADVANCE OF CHINESE COMPUTING TECHNOLOGIES | 2007年
关键词
anaphora resolution; coreference resolution; domain ontology; adaptive machine learning algorithm; semantic similarity feature;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a framework 4 anaphora resolution including coreference resolution based on domain ontology. To acquire better features and mine semantic relationships of entities in documents, we develop domain ontology and make use of ontology knowledge rather than flat gazetteers, proper lexicons or term lists. The basic steps that we put forward are: creating domain ontology seeds; training resolution model by adopting adaptive Machine Learning algorithms; gaining new knowledge and recognizing anaphora relations. Then in section 5, we put forward the strategy of semantic similarity computing and expect to mine semantic similarity feature in specific domain with general linguistic ontology resource-HowNet(1), so as to improve the performance of NPs' coreference resolution. The concrete method is to acquire NPs' concept similarity from sememe similarity.
引用
收藏
页码:134 / 139
页数:6
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