Output details
11 - Computer Science and Informatics
University of Southampton
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Output 0 of 0 in the submission
Article title
SPEAR: spamming-resistant expertise analysis and ranking in collaborative tagging systems
Type
D - Journal article
Title of journal
Computational Intelligence
Article number
-
Volume number
27
Issue number
3
First page of article
458
ISSN of journal
0824-7935
Year of publication
2011
Number of additional authors
4
Additional information
Significance of output:
<16>This paper presents a novel method for identifying malicious contributors to collaborative tagging systems, by considering both co-tagging behaviour and timeliness. The method was evaluated using a combination of real-world data (from the Delicious social bookmarking site) and synthetic data, and was shown to significantly outperform traditional frequency counting and HITS-like approaches.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
1
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-