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© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 28. April 2022)
1Hagedorn, K. ; Chapman, S. ; Newman, D.: Enhancing search and browse using automated clustering of subject metadata.
In: D-Lib magazine. 13(2007) nos.7/8, x S.
Abstract: The Web puzzle of online information resources often hinders end-users from effective and efficient access to these resources. Clustering resources into appropriate subject-based groupings may help alleviate these difficulties, but will it work with heterogeneous material? The University of Michigan and the University of California Irvine joined forces to test automatically enhancing metadata records using the Topic Modeling algorithm on the varied OAIster corpus. We created labels for the resulting clusters of metadata records, matched the clusters to an in-house classification system, and developed a prototype that would showcase methods for search and retrieval using the enhanced records. Results indicated that while the algorithm was somewhat time-intensive to run and using a local classification scheme had its drawbacks, precise clustering of records was achieved and the prototype interface proved that faceted classification could be powerful in helping end-users find resources.
Anmerkung: Vgl. auch: http://dlib.ukoln.ac.uk/dlib/july07/hagedorn/07hagedorn.html.
Themenfeld: Automatisches Klassifizieren
2Hagedorn, K.: OAIster: a "no dead ends" OAI service provider.
In: Library hi tech. 21(2003) no.2, S.170-181.
Abstract: OAIster, at the University of Michigan, University Libraries, Digital Library Production Service (DLPS), is an Andrew W. Mellon Foundation grant-funded project designed to test the feasibility of using the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) to harvest digital object metadata from multiple and varied digital object repositories and develop a service to allow end-users to access that metadata. This article describes in-depth the development of our system to harvest, store, transform the metadata into Digital Library eXtension Service (DLXS) Bibliographic Class format, build indexes and make the metadata searchable through an interface using the XPAT search engine. Results of the testing of our service and statistics on usage are reported, as well as the issues that we have encountered during our harvesting and transformation operations. The article closes by discussing the future improvements and potential of OAIster and the OAI-PMH protocol.
Inhalt: Vgl. auch unter: http://www.emeraldinsight.com/10.1108/07378830310479811.