RESEARCH ON AUTOMATIC SEMANTIC CLASSIFICATION OF HUMAN-INTERACTION INSTRUCTIONS
Instructions extraction extracts structured information from unstructured natural language instruction text,is an application of information extraction in the field of human-computer interaction.For a natural language instruction text,if we want to extract structural information which can able to describe the text semantic completely,it is critical to position these words or phrases and mark one description which belongs to their own semantic description.This paper first try to a solution which is semantic classification based on dictionary.Because of some shortcomings of the dictionary itself,the semantic classification results are poor.Through the analysis of dictionary-based semantic classification results,this paper proposes a semantic classification method which combining CRF,self-training and Dictionary.Use this method to conduct experiments in the field of vehicle.The experiment results show that our method can be effective in semantic classification for the natural language instruction text; the overall correct rate is 92%.Semantic classification is prepared for the following work of structured information extraction.
Instruction extraction Information extraction Semantic classification Structurization Human-computer interaction CRF Self-training
Shuming Yuan Xiaojie Wang
Laboratory of Intelligent science and technology,Beijing University of Posts and Telecommunications,Beijing 100876,China
国际会议
杭州
英文
1896-1901
2012-10-30（万方平台首次上网日期，不代表论文的发表时间）