Managing computer files via artificial intelligence approaches
Jin, X, Jiang, J and Min, G (2009) Managing computer files via artificial intelligence approaches Artificial Intelligence Review, 31 (1-4). pp. 101-117.
Full text not available from this repository.Abstract
Agent-oriented computing has been regarded as a very promising methodology to developing intelligent software systems. Intelligent agent technology has, thus, been successfully applied in many industrial and commercial areas. Cased based reasoning (CBR) is an effective and efficient analogical reasoning method for solving problems using the knowledge of past experiences, which are stored in a knowledge base as cases. CBR has been extensively employed to tackle such problems as design, planning, classification, and advising in many different application fields. On the other hand, as various files are created on computers, how to efficiently manage computer files becomes a significant issue. So far, there are a number of file management systems available. However, none of them can deal with these crucial problems of file management: Which files should be deleted after their use? Which files should be temporarily kept or permanently preserved? To the best of our knowledge, these problems have not yet been investigated in the open literature. To bridge this gap, in this paper we explore the value of the above artificial intelligence approaches in managing computer files. We develop an intelligent agent based personal file management system, where CBR is employed to guide users to managing their files. Through extensive practical experiments, we validate the effectiveness and efficiency of the developed system.
Item Type: | Article | ||||||||||||
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Divisions : | Surrey research (other units) | ||||||||||||
Authors : |
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Date : | 2009 | ||||||||||||
DOI : | 10.1007/s10462-009-9129-2 | ||||||||||||
Depositing User : | Symplectic Elements | ||||||||||||
Date Deposited : | 17 May 2017 12:25 | ||||||||||||
Last Modified : | 24 Jan 2020 22:12 | ||||||||||||
URI: | http://epubs.surrey.ac.uk/id/eprint/835267 |
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