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To Tag or Not to Tag Harvesting Adjacent Metadata in Large-Scale Tagging Systems *
 

Summary: To Tag or Not to Tag ­ Harvesting Adjacent Metadata in
Large-Scale Tagging Systems *
Adriana Budura , Sebastian Michel , Philippe Cudré-Mauroux , Karl Aberer
EPFL, Switzerland MIT, USA
firstname.lastname@epfl.ch pcm@csail.mit.edu
ABSTRACT
We present HAMLET, a suite of principles, scoring models
and algorithms to automatically propagate metadata along
edges in a document neighborhood. As a showcase sce-
nario we consider tag prediction in community-based Web
2.0 tagging applications. Experiments using real-world data
demonstrate the viability of our approach in large-scale en-
vironments where tags are scarce. To the best of our knowl-
edge, HAMLET is the first system to promote an efficient
and precise reuse of shared metadata in highly dynamic,
large-scale Web 2.0 tagging systems.
Categories and Subject Descriptors H.3.3 [Information
Storage and Retrieval]: Information Search and Retrieval--
Retrieval Models; H.m [Information Systems]: Miscellaneous
General Terms Algorithms, Design

  

Source: Aberer, Karl - Faculté Informatique et Communications, Ecole Polytechnique Fédérale de Lausanne
Massachusetts Institute of Technology (MIT), Department of Electrical Engineering and Computer Science, Database Group

 

Collections: Computer Technologies and Information Sciences