Using latent semantic analysis to improve access to textual information
CHI '88 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Rank, decomposition, and uniqueness for 3-way and n-way arrays
Multiway data analysis
Link prediction approach to collaborative filtering
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Higher-Order Web Link Analysis Using Multilinear Algebra
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
ACM SIGKDD Explorations Newsletter
The case for anomalous link discovery
ACM SIGKDD Explorations Newsletter
Dealing with Class Skew in Context Recognition
ICDCSW '06 Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems
The link-prediction problem for social networks
Journal of the American Society for Information Science and Technology
Predicting who rated what in large-scale datasets
ACM SIGKDD Explorations Newsletter - Special issue on visual analytics
Lessons from the Netflix prize challenge
ACM SIGKDD Explorations Newsletter - Special issue on visual analytics
Augmenting the power of LSI in text retrieval: Singular value rescaling
Data & Knowledge Engineering
Efficient MATLAB Computations with Sparse and Factored Tensors
SIAM Journal on Scientific Computing
Local Probabilistic Models for Link Prediction
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Unsupervised Multiway Data Analysis: A Literature Survey
IEEE Transactions on Knowledge and Data Engineering
Temporal-Relational Classifiers for Prediction in Evolving Domains
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
The Time-Series Link Prediction Problem with Applications in Communication Surveillance
INFORMS Journal on Computing
Collaborative filtering with temporal dynamics
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Tensor Decompositions and Applications
SIAM Review
Link Prediction on Evolving Data Using Matrix and Tensor Factorizations
ICDMW '09 Proceedings of the 2009 IEEE International Conference on Data Mining Workshops
Collective sampling and analysis of high order tensors for chatroom communications
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
Link prediction via matrix factorization
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Tensor factorization using auxiliary information
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Role-dynamics: fast mining of large dynamic networks
Proceedings of the 21st international conference companion on World Wide Web
Time-Evolving relational classification and ensemble methods
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Dynamic pagerank using evolving teleportation
WAW'12 Proceedings of the 9th international conference on Algorithms and Models for the Web Graph
Fast similarity computation in factorized tensors
SISAP'12 Proceedings of the 5th international conference on Similarity Search and Applications
Proceedings of the 21st ACM international conference on Information and knowledge management
Expanders, tropical semi-rings, and nuclear norms: oh my!
XRDS: Crossroads, The ACM Magazine for Students - Scientific Computing
Exploiting homophily effect for trust prediction
Proceedings of the sixth ACM international conference on Web search and data mining
Modeling dynamic behavior in large evolving graphs
Proceedings of the sixth ACM international conference on Web search and data mining
A hidden Markov model for collaborative filtering
MIS Quarterly
Who proposed the relationship?: recovering the hidden directions of undirected social networks
Proceedings of the 23rd international conference on World wide web
Internal link prediction: A new approach for predicting links in bipartite graphs
Intelligent Data Analysis - Dynamic Networks and Knowledge Discovery
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The data in many disciplines such as social networks, Web analysis, etc. is link-based, and the link structure can be exploited for many different data mining tasks. In this article, we consider the problem of temporal link prediction: Given link data for times 1 through T, can we predict the links at time T + 1? If our data has underlying periodic structure, can we predict out even further in time, i.e., links at time T + 2, T + 3, etc.? In this article, we consider bipartite graphs that evolve over time and consider matrix- and tensor-based methods for predicting future links. We present a weight-based method for collapsing multiyear data into a single matrix. We show how the well-known Katz method for link prediction can be extended to bipartite graphs and, moreover, approximated in a scalable way using a truncated singular value decomposition. Using a CANDECOMP/PARAFAC tensor decomposition of the data, we illustrate the usefulness of exploiting the natural three-dimensional structure of temporal link data. Through several numerical experiments, we demonstrate that both matrix- and tensor-based techniques are effective for temporal link prediction despite the inherent difficulty of the problem. Additionally, we show that tensor-based techniques are particularly effective for temporal data with varying periodic patterns.