Research On Information Resource Management And Knowledge Discovery Based On DL

Aiming at information resources construction of digital library, the methods of information organizing and data mining are studied.First, the characteristics of information resources of digital library are given, the restrictions of general catalogue in describing networks information are shown. The metadata methods of describing networks information resources are expatiated. The definition, type, structure, coding language of metadata are presented. The interaction of metadata is researched. The application of typical metadata Dublin core is analyzed. The element formation of Dublin core is studied. The differences between Dublin core and general catalogue are compared. The networks information resource catalogue is discussed.Secondly, for data mining aspect of networks information, fuzzy vector space model is shown. The methods of fuzzy characteristic extracting and fuzzy characteristic vector constructing are presented. Three clustering algorithms are presented, these algorithms are as follows: k-means clustering algorithm, kernel clustering algorithm and ant cluster intelligence clustering algorithm.These clustering algorithms are based on fuzzy vector space model. Applying theory of fuzzy logic, neural networks and machine learning in artificial intelligence fields, three classification algorithms are presented, these algorithms are as follows: document automatic classification method based on weighting fuzzy reasoning networks, document automatic classification method based on self-organization feature mapping networks, document automatic classification method based on suppert vector machine. Each of algorithms gives detailed classification principle and approach. The availability of the algorithms is proved by experiment.Finally, a few countermeasures of reinforcing DL management and knowledge discovery are presented.