Inferring Web communities from link topology
Proceedings of the ninth ACM conference on Hypertext and hypermedia : links, objects, time and space---structure in hypermedia systems: links, objects, time and space---structure in hypermedia systems
Nymble: a high-performance learning name-finder
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Probabilistic classification and clustering in relational data
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Tractable Group Detection on Large Link Data Sets
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Link mining: a new data mining challenge
ACM SIGKDD Explorations Newsletter
Modeling and predicting personal information dissemination behavior
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Leveraging relational autocorrelation with latent group models
MRDM '05 Proceedings of the 4th international workshop on Multi-relational mining
Iteratively clustering web images based on link and attribute reinforcements
Proceedings of the 13th annual ACM international conference on Multimedia
Leveraging Relational Autocorrelation with Latent Group Models
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
ACM SIGKDD Explorations Newsletter
Group and topic discovery from relations and text
Proceedings of the 3rd international workshop on Link discovery
Topic evolution and social interactions: how authors effect research
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Finding tribes: identifying close-knit individuals from employment patterns
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining for offender group detection and story of a police operation
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
Structured machine learning: the next ten years
Machine Learning
The KOJAK group finder: connecting the dots via integrated knowledge-based and statistical reasoning
IAAI'04 Proceedings of the 16th conference on Innovative applications of artifical intelligence
Learning systems of concepts with an infinite relational model
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Data clustering with a relational push-pull model
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Topic and role discovery in social networks with experiments on enron and academic email
Journal of Artificial Intelligence Research
Joint group and topic discovery from relations and text
ICML'06 Proceedings of the 2006 conference on Statistical network analysis
Computationally efficient scoring of activity using demographics and connectivity of entities
Information Technology and Management
Using friendship ties and family circles for link prediction
SNAKDD'08 Proceedings of the Second international conference on Advances in social network mining and analysis
How is the Semantic Web evolving? A dynamic social network perspective
Computers in Human Behavior
Clustering scientific literature using sparse citation graph analysis
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Discovering overlapping communities of named entities
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Traffic models for community-based ranking and navigation
WINE'05 Proceedings of the First international conference on Internet and Network Economics
Discovering factions in the computational linguistics community
ACL '12 Proceedings of the ACL-2012 Special Workshop on Rediscovering 50 Years of Discoveries
Transforming graph data for statistical relational learning
Journal of Artificial Intelligence Research
A game theory based approach for community detection in social networks
BNCOD'13 Proceedings of the 29th British National conference on Big Data
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Link detection and analysis has long been important in the social sciences and in the government intelligence community. A significant effort is focused on the structural and functional analysis of "known" networks. Similarly, the detection of individual links is important but is usually done with techniques that result in "known" links. More recently the internet and other sources have led to a flood of circumstantial data that provide probabilistic evidence of links. Co-occurrence in news articles and simultaneous travel to the same location are two examples.We propose a probabilistic model of link generation based on membership in groups. The model considers both observed link evidence and demographic information about the entities. The parameters of the model are learned via a maximum likelihood search. In this paper we describe the model and then show several heuristics that make the search tractable. We test our model and optimization methods on synthetic data sets with a known ground truth and a database of news articles.