Probabilistic reasoning in intelligent systems: networks of plausible inference
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Learning and relearning in Boltzmann machines
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
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Artificial Intelligence - Special issue on relevance
Enhanced hypertext categorization using hyperlinks
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Learning to extract symbolic knowledge from the World Wide Web
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Probabilistic frame-based systems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Activity monitoring: noticing interesting changes in behavior
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining: practical machine learning tools and techniques with Java implementations
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Co-clustering documents and words using bipartite spectral graph partitioning
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Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic Networks and Expert Systems
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Relational Data Mining
Three companions for data mining in first order logic
Relational Data Mining
Propositionalization approaches to relational data mining
Relational Data Mining
Data Mining and Knowledge Discovery
Automating the Construction of Internet Portals with Machine Learning
Information Retrieval
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Crafting Papers on Machine Learning
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Learning Probabilistic Relational Models
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Learning from Labeled and Unlabeled Data using Graph Mincuts
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Dependency networks for inference, collaborative filtering, and data visualization
The Journal of Machine Learning Research
Tree induction vs. logistic regression: a learning-curve analysis
The Journal of Machine Learning Research
Aggregation-based feature invention and relational concept classes
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning relational probability trees
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
ACM Transactions on Information Systems (TOIS)
Why collective inference improves relational classification
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Semi-supervised learning using randomized mincuts
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Learning associative Markov networks
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Naive Bayesian Classification of Structured Data
Machine Learning
Dependency Networks for Relational Data
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Using relational knowledge discovery to prevent securities fraud
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Leveraging Relational Autocorrelation with Latent Group Models
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Machine Learning
Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability)
Relational Dependency Networks
The Journal of Machine Learning Research
Probabilistic classification and clustering in relational data
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Loopy belief propagation for approximate inference: an empirical study
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Discriminative probabilistic models for relational data
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Social ties and their relevance to churn in mobile telecom networks
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Effective label acquisition for collective classification
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Using ghost edges for classification in sparsely labeled networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Structured machine learning: the next ten years
Machine Learning
A bias/variance decomposition for models using collective inference
Machine Learning
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ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Classifying networked entities with modularity kernels
Proceedings of the 17th ACM conference on Information and knowledge management
Web page classification: Features and algorithms
ACM Computing Surveys (CSUR)
Towards Machine Learning on the Semantic Web
Uncertainty Reasoning for the Semantic Web I
Improving music genre classification using collaborative tagging data
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Graph nodes clustering with the sigmoid commute-time kernel: A comparative study
Data & Knowledge Engineering
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Graffiti: node labeling in heterogeneous networks
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Heterogeneous source consensus learning via decision propagation and negotiation
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Relational learning via latent social dimensions
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
A Fast Method for Property Prediction in Graph-Structured Data from Positive and Unlabelled Examples
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Simulated Iterative Classification A New Learning Procedure for Graph Labeling
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Within-Network Classification Using Local Structure Similarity
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Improving learning in networked data by combining explicit and mined links
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Reflect and correct: A misclassification prediction approach to active inference
ACM Transactions on Knowledge Discovery from Data (TKDD)
Scalable learning of collective behavior based on sparse social dimensions
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An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting
DS '09 Proceedings of the 12th International Conference on Discovery Science
Homophily of Neighborhood in Graph Relational Classifier
SOFSEM '10 Proceedings of the 36th Conference on Current Trends in Theory and Practice of Computer Science
Social network classification incorporating link typevalues
ISI'09 Proceedings of the 2009 IEEE international conference on Intelligence and security informatics
Cautious Collective Classification
The Journal of Machine Learning Research
Proceedings of the 19th international conference on World wide web
Multi-network fusion for collective inference
Proceedings of the Eighth Workshop on Mining and Learning with Graphs
Network quantification despite biased labels
Proceedings of the Eighth Workshop on Mining and Learning with Graphs
Computationally efficient scoring of activity using demographics and connectivity of entities
Information Technology and Management
Link homophily in the application layer and its usage in traffic classification
INFOCOM'10 Proceedings of the 29th conference on Information communications
A Very Fast Method for Clustering Big Text Datasets
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Combining link and content for collective active learning
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
SNAKDD'08 Proceedings of the Second international conference on Advances in social network mining and analysis
Graph regularized transductive classification on heterogeneous information networks
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Label-dependent feature extraction in social networks for node classification
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A method of label-dependent feature extraction in social networks
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From bias to opinion: a transfer-learning approach to real-time sentiment analysis
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On the semantic annotation of places in location-based social networks
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Correcting bias in statistical tests for network classifier evaluation
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Data Mining and Knowledge Discovery
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Information Sciences: an International Journal
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EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
Label-dependent node classification in the network
Neurocomputing
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WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
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Information Sciences: an International Journal
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Pattern Recognition Letters
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This paper is about classifying entities that are interlinked with entities for which the class is known. After surveying prior work, we present NetKit, a modular toolkit for classification in networked data, and a case-study of its application to networked data used in prior machine learning research. NetKit is based on a node-centric framework in which classifiers comprise a local classifier, a relational classifier, and a collective inference procedure. Various existing node-centric relational learning algorithms can be instantiated with appropriate choices for these components, and new combinations of components realize new algorithms. The case study focuses on univariate network classification, for which the only information used is the structure of class linkage in the network (i.e., only links and some class labels). To our knowledge, no work previously has evaluated systematically the power of class-linkage alone for classification in machine learning benchmark data sets. The results demonstrate that very simple network-classification models perform quite well---well enough that they should be used regularly as baseline classifiers for studies of learning with networked data. The simplest method (which performs remarkably well) highlights the close correspondence between several existing methods introduced for different purposes---that is, Gaussian-field classifiers, Hopfield networks, and relational-neighbor classifiers. The case study also shows that there are two sets of techniques that are preferable in different situations, namely when few versus many labels are known initially. We also demonstrate that link selection plays an important role similar to traditional feature selection.