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Semantic Tag Recommendation Using Concept Model Chenliang Li, Anwitaman Datta, Aixin Sun
 

Summary: Semantic Tag Recommendation Using Concept Model
Chenliang Li, Anwitaman Datta, Aixin Sun
School of Computer Engineering, Nanyang Technological University, Singapore
{lich0020|anwitaman|axsun}@ntu.edu.sg
ABSTRACT
The common tags given by multiple users to a particular document
are often semantically relevant to the document and each tag repre-
sents a specific topic. In this paper, we attempt to emulate human
tagging behavior to recommend tags by considering the concepts
contained in documents. Specifically, we represent each document
using a few most relevant concepts contained in the document,
where the concept space is derived from Wikipedia. Tags are then
recommended based on the tag concept model derived from the an-
notated documents of each tag. Evaluated on a Delicious dataset of
more than 53K documents, the proposed technique achieved com-
parable tag recommendation accuracy as the state-of-the-art, while
yielding an order of magnitude speed-up.
Categories and Subject Descriptors
H.3.1 [Information Systems]: Information Search and Retrieval--
Content Analysis and Indexing

  

Source: Aixin, Sun - School of Computer Engineering, Nanyang Technological University

 

Collections: Computer Technologies and Information Sciences