DocumentCode :
2540157
Title :
Geodesic search and retrieval of semi-structured databases
Author :
Rubin, Stuart H. ; Chen, Shu-Ching
Author_Institution :
SPAWAR Syst. Center, San Diego
fYear :
2007
fDate :
7-10 Oct. 2007
Firstpage :
3396
Lastpage :
3401
Abstract :
This paper addresses the learning of search-control knowledge expressed in semi-structured natural language. That knowledge is mined from semi-structured databases and applied to search the same. As is the case with most self-referential systems, this process necessarily addresses the issues of randomization, representation, machine learning, and evolutionary programming. Machine learning becomes pervasive at all levels of representation. That is, the randomization of knowledge necessarily includes that of its representation. Application to the search and retrieval of multimedia databases is suggested.
Keywords :
evolutionary computation; information retrieval; learning (artificial intelligence); multimedia databases; natural language processing; evolutionary programming; geodesic retrieval; geodesic search; machine learning; multimedia databases; representation; search-control knowledge learning; semistructured databases; semistructured natural language; Annealing; Data mining; Information retrieval; Machine learning; Multimedia databases; Natural languages; Neural networks; Relational databases; Spatial databases; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
978-1-4244-0990-7
Electronic_ISBN :
978-1-4244-0991-4
Type :
conf
DOI :
10.1109/ICSMC.2007.4413649
Filename :
4413649
Link To Document :
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