Title :
Intelligent query and browsing information retrieval (IQBIR) agent
Author_Institution :
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
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;
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4428-6
DOI :
10.1109/ICASSP.1998.675479
