Uniform Techniques for Deriving Similarities of Objects and Subschemes in Heterogeneous Databases
IEEE Transactions on Knowledge and Data Engineering
Similarity-based estimation of word cooccurrence probabilities
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Integration of XML schemas at various "severity" levels
Information Systems
Duplicate Record Detection: A Survey
IEEE Transactions on Knowledge and Data Engineering
The link-prediction problem for social networks
Journal of the American Society for Information Science and Technology
Eliminating fuzzy duplicates in data warehouses
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Growth of the flickr social network
Proceedings of the first workshop on Online social networks
The convergence of social and technological networks
Communications of the ACM - Remembering Jim Gray
User identification for cross-system personalisation
Information Sciences: an International Journal
APWEB '10 Proceedings of the 2010 12th International Asia-Pacific Web Conference
Human mobility, social ties, and link prediction
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Probabilistic Subgraph Matching on Huge Social Networks
ASONAM '11 Proceedings of the 2011 International Conference on Advances in Social Networks Analysis and Mining
As time goes by: discovering eras in evolving social networks
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Crawling Social Internetworking Systems
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Bridge analysis in a Social Internetworking Scenario
Information Sciences: an International Journal
International Journal of Web Based Communities
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Distinct social networks are interconnected via bridge users, who play thus a key role when crossing information is investigated in the context of Social Internetworking analysis. Unfortunately, not always users make their role of bridge explicit by specifying the so-called me edge (i.e., the edge connecting the accounts of the same user in two distinct social networks), missing thus a potentially very useful information. As a consequence, discovering missing me edges is an important problem to face in this context yet not so far investigated. In this paper, we propose a common-neighbors approach to detecting missing me edges, which returns good results in real life settings. Indeed, an experimental campaign shows both that the state-of-the-art common-neighbors approaches cannot be effectively applied to our problem and, conversely, that our approach returns precise and complete results.