Probabilistic Horn abduction and Bayesian networks
Artificial Intelligence
Answering queries from context-sensitive probabilistic knowledge bases
Selected papers from the international workshop on Uncertainty in databases and deductive systems
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
A tutorial on learning with Bayesian networks
Learning in graphical models
Proceedings of the 1998 conference on Advances in neural information processing systems II
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Learning Belief Networks in the Presence of Missing Values and Hidden Variables
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Learning probabilities for noisy first-order rules
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Generalized Stochastic Tree Automata for Multi-relational Data Mining
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Learning Probabilistic Relational Models
SARA '02 Proceedings of the 4th International Symposium on Abstraction, Reformulation, and Approximation
Propositionalisation and Aggregates
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
CL '00 Proceedings of the First International Conference on Computational Logic
ILP '00 Proceedings of the 10th International Conference on Inductive Logic Programming
Adaptive Bayesian Logic Programs
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Towards Combining Inductive Logic Programming with Bayesian Networks
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Learning with Concept Hierarchies in Probabilistic Relational Data Mining
WAIM '02 Proceedings of the Third International Conference on Advances in Web-Age Information Management
First-Order Probabilistic Languages: Into the Unknown
Inductive Logic Programming
Structure Learning of Probabilistic Relational Models from Incomplete Relational Data
ECML '07 Proceedings of the 18th European conference on Machine Learning
Feature Discovery with Type Extension Trees
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
Representing uncertain data: models, properties, and algorithms
The VLDB Journal — The International Journal on Very Large Data Bases
PrDB: managing and exploiting rich correlations in probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
Sequential inference with reliable observations: Learning to construct force-dynamic models
Artificial Intelligence
Classification of graphical data made easy
Neurocomputing
Compiling relational Bayesian networks for exact inference
International Journal of Approximate Reasoning
Increasing representational power and scaling reasoning in probabilistic databases
Proceedings of the 13th International Conference on Database Theory
FastInf: An Efficient Approximate Inference Library
The Journal of Machine Learning Research
ACM Transactions on Information Systems (TOIS)
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
Discovering missing values in semi-structured databases
Large Scale Semantic Access to Content (Text, Image, Video, and Sound)
Model failure and context switching using logic-based stochastic
Journal of Computer Science and Technology
Boosting learning and inference in Markov logic through metaheuristics
Applied Intelligence
Predicate Logic Based Image Grammars for Complex Pattern Recognition
International Journal of Computer Vision
HotACI'06 Proceedings of the First international conference on Hot topics in autonomic computing
Learning statistical models from relational data
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Declarative programming for agent applications
Autonomous Agents and Multi-Agent Systems
Patterns discovery for efficient structured probabilistic inference
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
Learning bayesian network structure from massive datasets: the «sparse candidate« algorithm
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Learning the dimensionality of hidden variables
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Inferring privacy information from social networks
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
Database security protection via inference detection
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
A unified context model: bringing probabilistic models to context ontology
EUC'05 Proceedings of the 2005 international conference on Embedded and Ubiquitous Computing
A semi-open learning environment for virtual laboratories
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Towards an integrated protein-protein interaction network
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
Understanding tuberculosis epidemiology using structured statistical models
Artificial Intelligence in Medicine
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Fundamenta Informaticae - Progress on Multi-Relational Data Mining
Using enterprise architecture analysis and interview data to estimate service response time
The Journal of Strategic Information Systems
Selectivity estimation for hybrid queries over text-rich data graphs
Proceedings of the 16th International Conference on Extending Database Technology
Top-k queries over web applications
The VLDB Journal — The International Journal on Very Large Data Bases
Automated probabilistic modeling for relational data
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Type Extension Trees for feature construction and learning in relational domains
Artificial Intelligence
From machine learning to machine reasoning
Machine Learning
Hi-index | 0.00 |
A large portion of real-world data is stored in commercial relational database systems. In contrast, most statistical learning methods work only with "flat" data representations. Thus, to apply these methods, we are forced to convert our data into a flat form, thereby losing much of the relational structure present in our database. This paper builds on the recent work on probabilistic relational models (PRMs), and describes how to learn them from databases. PRMs allow the properties of an object to depend probabilistically both on other properties of that object and on properties of related objects. Although PRMs are significantly more expressive than standard models, such as Bayesian networks, we show how to extend well-known statistical methods for learning Bayesian networks to learn these models. We describe both parameter estimation and structure learning -- the automatic induction of the dependency structure in a model. Moreover, we show how the learning procedure can exploit standard database retrieval techniques for efficient learning from large datasets. We present experimental results on both real and synthetic relational databases.