Intelligent query and browsing information retrieval (IQBIR) agent

Author

Park, Jong-Min

Author_Institution

Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA

Volume

2

fYear

1998

fDate

12-15 May 1998

Firstpage

1173

Abstract

Reported in this paper is an intelligent agent that aids users to conduct efficient Internet Web information retrieval through query formulation, information collection, information clustering, and analysis. The underlying mechanism is a probabilistic sample-at-the-boundary learning algorithm for clustering the search results and learning and matching the user concept. Kohonen´s (1990, 1992) “windowed” learning vector quantization algorithm is shown to be related to this sample-at-the-boundary learning algorithm. A prototype system has been developed and evaluation has been conducted

Keywords

Internet; cooperative systems; information retrieval; learning (artificial intelligence); online front-ends; pattern classification; self-organising feature maps; signal sampling; software agents; vector quantisation; Internet Web information retrieval; Kohonen´s LVQ algorithm; browsing information retrieval agent; information analysis; information clustering; information collection; intelligent query agent; probabilistic algorithm; prototype system; query formulation; sample-at-the-boundary learning algorithm; search results clustering; user concept learning; user concept matching; windowed learning vector quantization algorithm; Clustering algorithms; Displays; Feedback; Information retrieval; Intelligent agent; Learning systems; Search engines; Uniform resource locators; User interfaces; Web pages;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on

Conference_Location

Seattle, WA

ISSN

1520-6149

Print_ISBN

0-7803-4428-6

Type

conf

DOI

10.1109/ICASSP.1998.675479

Filename

675479