Title :
Concept similarity analysis in Ontology´s automatic extraction
Author_Institution :
Sch. of Inf., Linyi Normal Univ., Linyi, China
Abstract :
Ontology´s automatic extraction is a core problem of information integration in electronic government affair. In the process of ontology´s automatic extraction, FCA method is used in analyzing relationships between concepts automatically. But this method´s ability is insufficient in the analysis of the synonym relationship. This paper optimizes the FCA method and brings forward a new algorithm - SFCA. SFCA sets the weight for the attribute based on the importance of it. It computes the similarity degree using the weights and judges whether the concepts are synonymous. Through the analysis of the experiment´s result, the algorithm is validated to be effective. And its correctness proof is proved.
Keywords :
government data processing; information retrieval; matrix algebra; ontologies (artificial intelligence); SFCA; automatic ontology extraction; concept similarity analysis; electronic government affair; incidence matrix; information integration; information retrieval; synonym formal concept analysis; synonym relationship; Algorithm design and analysis; Data mining; Electronic government; Inference algorithms; Inference mechanisms; Information analysis; Information retrieval; Ontologies; Optimization methods; Wrapping; Automatic extraction; FCA; Information Integration; Ontology; SFCA;
Conference_Titel :
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4519-6
Electronic_ISBN :
978-1-4244-4520-2
DOI :
10.1109/ICCSIT.2009.5234574
