DocumentCode :
2243937
Title :
Research on automatic semantic classification of human-interaction instructions
Author :
Shuming Yuan ; Xiaojie Wang
Author_Institution :
Lab. of Intell. Sci. & Technol., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2012
fDate :
Oct. 30 2012-Nov. 1 2012
Firstpage :
1414
Lastpage :
1419
Abstract :
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.
Keywords :
classification; human computer interaction; information retrieval; natural language processing; text analysis; automatic semantic classification method; dictionary-based semantic classification analysis; human-computer interaction; human-interaction instructions; instructions extraction; structured information extraction; text semantic description; unstructured natural language instruction text; Context; Data mining; Dictionaries; Natural languages; Semantics; Tagging; Vehicles; CRF; human-computer interaction; information extraction; instruction extraction; self-training; semantic classification; structurization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-1855-6
Type :
conf
DOI :
10.1109/CCIS.2012.6664618
Filename :
6664618
Link To Document :
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