Title :
Searching of brief message based on semantic context
Author :
GuangJun Huang ; Musilek, Petr
Author_Institution :
Sch. of Electr. & Inf. Eng., Henan Univ. of Sci. & Technol., Luoyang
Abstract :
There are a lot of brief semi-structure messages in the Internet. A semantic matching method based on contexts of concepts is proposed. Each word of space vectors representing brief messages is extended with synonyms in a controlled process according to the scores of information gains. Patterns of messages are extracted with naive Bayesian classifier. The similarity between a query and the message is measured by combining knowledge of their hierarchical structures with statistics on their actual usage in messages derived from a large corpus. The experiment result indicates the method has significantly improved the precision of retrieval systems.
Keywords :
Bayes methods; Internet; information retrieval; pattern classification; Internet; brief messages; information gains; naive Bayesian classifier; retrieval systems; semantic context; semantic matching method; semi-structure messages; space vectors; Bayesian methods; Data mining; Internet; Mechatronics; Pattern matching; Process control; Search engines; Space technology; Statistics; Taxonomy; Bayesian Classifier; Information Gains; semantic contexts; semantic similarity;
Conference_Titel :
Mechatronics and Automation, 2008. ICMA 2008. IEEE International Conference on
Conference_Location :
Takamatsu
Print_ISBN :
978-1-4244-2631-7
Electronic_ISBN :
978-1-4244-2632-4
DOI :
10.1109/ICMA.2008.4798851
