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LearnMiner: deductive, tolerant agents for discovering didactic resources on the web
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Source SEKE; Vol. 27 archive
Proceedings of the 14th international conference on Software engineering and knowledge engineering table of contents
Ischia, Italy
SESSION: Soft computing table of contents
Pages: 109 - 115  
Year of Publication: 2002
ISBN:1-58113-556-4
Authors
Vincenzo Loia  Universita' di Salerno, S. Allende - 84081 Baronissi, (SA), Italy
Sabrina Senatore  Universita' di Salerno, S. Allende - 84081 Baronissi, (SA), Italy
M. I. Sessa  Universita' di Salerno, S. Allende - 84081 Baronissi, (SA), Italy
Publisher
ACM  New York, NY, USA
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ABSTRACT

As information nowadays represents a key factor in every successful business, and Internet offers literally tons of available data concerning almost every area of human activity, there emerges a real necessity for good search tools that can obtain high quality information in a short time. Nowadays finding useful information can be an overwhelming task. As a result, consumers need effective mechanisms for searching the Web. This paper describes LearnMiner, an open, agent-based platform designed for advanced didactic resource discovery. A central role is played by deductive agents, equipped with a similarity-based inference mechanism. This issue enables to bridge the gap between the requested information and the available information on the net, considering the "similarity" as a weaker relation for undiscernibility.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Vincenzo Loia: colleagues
Sabrina Senatore: colleagues
M. I. Sessa: colleagues