SREC: Discourse-level semantic relation extraction from text
作者： Mohammad-hadi Zahedi , Mohsen Kahani
DOI: 10.1007/S00521-012-1109-9
关键词: Artificial intelligence 、 Semantic search 、 Semantic similarity 、 Semantic computing 、 Semantic equivalence 、 Semantic Web 、 Explicit semantic analysis 、 Relationship extraction 、 Probabilistic latent semantic analysis 、 Semantic technology 、 Automatic summarization 、 Information retrieval 、 Text graph 、 Computer science 、 Natural language processing 、 Semantic compression 、 Social Semantic Web 、 Text mining 、 Holonymy 、 Knowledge acquisition 、 Search engine
摘要: Semantic relation extraction is a significant topic in semantic web and natural language processing with various important applications such as knowledge acquisition, text mining, information retrieval search engine, classification summarization. Many approaches rule base, machine learning statistical methods have been applied, targeting different types of ranging from hyponymy, hypernymy, meronymy, holonymy to domain-specific relation. In this paper, we present computational method for explicit implicit text, by applying statistic linear algebraic besides syntactic text.
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