Geodesic search and retrieval of semi-structured databases

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 rand...

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Bibliographic Details
Main Authors: Rubin, S.H., Shu-Ching Chen
Format: Conference Proceeding
Language:English
Subjects:
Annealing
Data mining
Information retrieval
Machine learning
Multimedia databases
Natural languages
Neural networks
Relational databases
Spatial databases
Testing
Online Access:Request full text
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Summary: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.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.2007.4413649