Ein englischer Text von Adam Mathes mit den Themen:The Creation of Metadata, Tagging Content in Del.icio.us and Flickr, From Tags to Folksonomy, Why Folksonomies Work and Areas For Further Research
Scalable and Efficient Data Streaming Algorithms for Detecting Common Content in Internet Traffic. Minho Sung, Abhishek Kumar, Li Li, Jia Wang, Jun Xu. To appear in the Proc. of 2nd IEEE International Workshop on Networking Meets Databases (NetDB'06), April 2006. Sketch Guided Sampling -- Using On-Line Estimates of Flow Size for Adaptive Data Collection. Abhishek Kumar, Jun (Jim) Xu. To appear in the proceedings of IEEE Infocom'06, Barcelona, Spain, April 2006.
LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM.
Main features of LIBLINEAR include
* Same data format as LIBSVM, our general-purpose SVM solver, and also similar usage
* Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer
* Cross validation for model selection
* Probability estimates (logistic regression only)
* Weights for unbalanced data
* MATLAB/Octave, Java interfaces
Advantages and drawbacks of data organisation in hierarchies, facets and with tags. Problems with finding the needed data without exact knowledge about it.
"by letting users tag (...), we're (building) systems that, like the Web itself, do a better job of letting individuals create value for one another, often without realizing it."
While professionally created metadata are often considered of high quality, it is costly in terms of time and effort to produce. User created metadata is a third approach, and this paper focuses on grassroots community classification of digital assets.
Dewey.info is an experimental space for linked DDC data. The initial data set available is a
linked data version of the DDC Summaries in nine languages. The intention of the dewey.info prototype
is to be a platform for Dewey data on the Web.
There are many different folk tales in the world, but many tales are variations on a limited number of themes. The classification system originally designed by Aarne, and later revised first by Thompson and later by Uther, is intended to bring out the similarities between tales by grouping variants of the same tale under the same ATU category. like hraf
The Cataloging Lab is a place for catalogers and anyone who cares about library metadata to experiment with creating better controlled vocabularies. Suggesting additions and changes to the Library of Congress Subject Headings vocabulary can be an isolating endeavor—it can be difficult to determine if your heading has already been proposed or if someone else is working on a proposal at the same time you are. The Cataloging Lab is designed to be a wiki where folks can collaborate on headings together to create stronger proposals.
Diese Einführung soll die Nutzung der Beschreibungssprache Simple Knowledge Organization System (SKOS) für kontrollierte Vokabulare erleichtern. Wir diskutieren den Zweck und die Vorteile am Beispiel von Open Educational Resources (OER).
Diese Seite beinhaltet einen theoretischen Überblick. Wer direkt praktisch einsteigen möchte, kann im Tutorial ein SKOS-Vokabular von Grund auf erstellen und veröffentlichen.
There is no official classification of prokaryotes, but the names given to prokaryotes are regulated. This website includes the nomenclature of prokaryotes and the nomenclatural changes as cited in the literature.
Provides biodiversity knowledge about all known species, including their taxonomy, geographic distribution, collections, genetics, evolutionary history, morphology, behavior, ecological relationships, and importance for human well being.
Emily Drabinski , Queering the Catalog: Queer Theory and the Politics of Correction, The Library Quarterly: Information, Community, Policy, Vol. 83, No. 2 (April 2013), pp. 94-111
X. Zhang, and Y. LeCun. (2015)cite arxiv:1502.01710Comment: This technical report is superseded by a paper entitled "Character-level Convolutional Networks for Text Classification", arXiv:1509.01626. It has considerably more experimental results and a rewritten introduction.