Paper Info
Title
A Comparison of Generated Wikipedia Profiles Using Social Labeling and Automatic Keyword Extraction
Abstract
In many collaborative systems, researchers are interested in creating representative user profiles. In this paper, we are particularly interested in using social labeling and automatic keyword extraction techniques for generating user profiles. Social labeling is a process in which users manually tag other users with keywords. Automatic keyword extraction is a technique that selects the most salient words to represent a user's contribution. We apply each of these two profile generation methods to highly active Wikipedia editors and their contributions, and compare the results. We found that profiles generated through social labeling matches the profiles generated via automatic keyword extraction, and vice versa. The results suggest that user profiles generated from one method can be used as a seed or bootstrapping proxy for the other method.
Year
Venue
Field
2010
ICWSM
Data mining,Information retrieval,Bootstrapping,Computer science,Keyword extraction,Collaboration,Salient
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
7
3
Name
Order
Citations
PageRank
Terrell Russell1605.71
Bongwon Suh22203171.49
Ed H. Chi34806371.21