Title :
A machine learning approach to document retrieval: an overview and an experiment
Author_Institution :
Dept. of Manage. Inf. Syst., Arizona Univ., Tucson, AZ, USA
Abstract :
We provide an overview of artificial intelligence techniques and then present a machine learning based document retrieval system we developed. GANNET (Genetic Algorithms and Neural Nets System) performed concept (keyword) optimization for user-selected documents during document retrieval using genetic algorithms. It then used the optimized concepts to perform concept exploration in a large network of related concepts through the Hopfield net parallel relaxation procedure. Our preliminary experiment showed that GANNET helped improve search recall by identifying the underlying concepts (keywords) which best describe the user-selected documents.<>
Keywords :
Hopfield neural nets; database management systems; genetic algorithms; learning (artificial intelligence); query processing; GANNET; Hopfield net parallel relaxation procedure; artificial intelligence techniques; concept exploration; concept keyword optimization; document retrieval; genetic algorithm; keyword optimization; machine learning approach; machine learning based document retrieval system; neural nets; search recall; user-selected documents;
Conference_Titel :
System Sciences, 1994. Proceedings of the Twenty-Seventh Hawaii International Conference on
Conference_Location :
Wailea, HI, USA
Print_ISBN :
0-8186-5090-7
DOI :
10.1109/HICSS.1994.323318
