The NP-completeness column: An ongoing guide
Journal of Algorithms
Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
The discrete p-maxian location problem
Computers and Operations Research
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Similarity estimation techniques from rounding algorithms
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
The Journal of Machine Learning Research
Jelly: A Language for Building Community-Centric Information Exploration Applications
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Building community-centric information exploration applications on social content sites
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Speak the same language with your friends: augmenting tag recommenders with social relations
Proceedings of the 21st ACM conference on Hypertext and hypermedia
Connecting users and items with weighted tags for personalized item recommendations
Proceedings of the 21st ACM conference on Hypertext and hypermedia
Topic-based personalized recommendation for collaborative tagging system
Proceedings of the 21st ACM conference on Hypertext and hypermedia
Of categorizers and describers: an evaluation of quantitative measures for tagging motivation
Proceedings of the 21st ACM conference on Hypertext and hypermedia
Of kings, traffic signs and flowers: exploring navigation of tagged documents
Proceedings of the 21st ACM conference on Hypertext and hypermedia
The data analytics group at the qatar computing research institute
ACM SIGMOD Record
Exploratory mining of collaborative social content
Proceedings of the 2013 Sigmod/PODS Ph.D. symposium on PhD symposium
A personalized recommender system based on users' information in folksonomies
Proceedings of the 22nd international conference on World Wide Web companion
A framework for tag-aware recommender systems
Expert Systems with Applications: An International Journal
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The rise of Web 2.0 is signaled by sites such as Flickr, del.icio.us, and YouTube, and social tagging is essential to their success. A typical tagging action involves three components, user, item (e.g., photos in Flickr), and tags (i.e., words or phrases). Analyzing how tags are assigned by certain users to certain items has important implications in helping users search for desired information. In this paper, we explore common analysis tasks and propose a dual mining framework for social tagging behavior mining. This framework is centered around two opposing measures, similarity and diversity, being applied to one or more tagging components, and therefore enables a wide range of analysis scenarios such as characterizing similar users tagging diverse items with similar tags, or diverse users tagging similar items with diverse tags, etc. By adopting different concrete measures for similarity and diversity in the framework, we show that a wide range of concrete analysis problems can be defined and they are NP-Complete in general. We design efficient algorithms for solving many of those problems and demonstrate, through comprehensive experiments over real data, that our algorithms significantly out-perform the exact brute-force approach without compromising analysis result quality.