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Full-Text Articles in Databases and Information Systems
Modified Art 2a Growing Network Capable Of Generating A Fixed Number Of Nodes, Ji He, Ah-Hwee Tan, Chew-Lim Tan
Modified Art 2a Growing Network Capable Of Generating A Fixed Number Of Nodes, Ji He, Ah-Hwee Tan, Chew-Lim Tan
Research Collection School Of Computing and Information Systems
This paper introduces the Adaptive Resonance Theory under Constraint (ART-C 2A) learning paradigm based on ART 2A, which is capable of generating a user-defined number of recognition nodes through online estimation of an appropriate vigilance threshold. Empirical experiments compare the cluster validity and the learning efficiency of ART-C 2A with those of ART 2A, as well as three closely related clustering methods, namely online K-Means, batch K-Means, and SOM, in a quantitative manner. Besides retaining the online cluster creation capability of ART 2A, ART-C 2A gives the alternative clustering solution, which allows a direct control on the number of output …
Resource Harvesting Within The Oai-Pmh Framework, Herbert Van De Sompel, Michael L. Nelson, Carl Lagoze, Simeon Warner
Resource Harvesting Within The Oai-Pmh Framework, Herbert Van De Sompel, Michael L. Nelson, Carl Lagoze, Simeon Warner
Computer Science Faculty Publications
Motivated by preservation and resource discovery, we examine how digital resources, and not just metadata about resources, can be harvested using the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH). We review and critique existing techniques for identifying and gathering digital resources using metadata harvested through the OAI-PMH. We introduce an alternative solution that builds on the introduction of complex object formats that provide a more accurate way to describe digital resources. We argue that the use of complex object formats as OAI-PMH metadata formats results in a reliable and attractive approach for incremental harvesting of resources using the OAI-PMH.