A machine learning approach to document retrieval: an overview and an experiment

Author

Chen, H.

Author_Institution

Dept. of Manage. Inf. Syst., Arizona Univ., Tucson, AZ, USA

Volume

3

fYear

1994

fDate

4-7 Jan. 1994

Firstpage

631

Lastpage

640

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/HICSS.1994.323318

Filename

323318