Title :
Fuzzy model fragment retrieval
Author :
Fu, Xin ; Shen, Qiang
Author_Institution :
Dept. of Comput. Sci., Aberystwyth Univ., Aberystwyth
Abstract :
Given a set of collected evidence and a knowledge base, fuzzy compositional modelling (FCM) begins by retrieving model fragments which are the most likely to be relevant to the available data. Since FCM often involves imprecise and uncertain information, a match between the available data and the knowledge base cannot in general be done precisely, partial matching may suffice. This paper proposes a more flexible fuzzy model fragment retrieval mechanism to match data items with broader, including possibly subjective information in the knowledge base. It is capable of retrieving those model fragments that can approximately match the collected evidence, when no exact match occurs. The retrieval process and its capability is illustrated by means of an application example.
Keywords :
fuzzy set theory; information retrieval; knowledge based systems; pattern matching; fuzzy compositional modelling; fuzzy model fragment retrieval mechanism; knowledge base; pattern matching; Cameras; Computational efficiency; Computer science; Data structures; Explosives; Fuzzy sets; Information retrieval; Knowledge representation; Taxonomy; Uncertainty;
Conference_Titel :
Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1818-3
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2008.4630552