How Good is Recursive Bisection?
SIAM Journal on Scientific Computing
Automating the Construction of Internet Portals with Machine Learning
Information Retrieval
Learning Probabilistic Relational Models
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Partitioning Methods for Satisfiability Testing on Large Formulas
CADE-13 Proceedings of the 13th International Conference on Automated Deduction: Automated Deduction
Ruling Out PTAS for Graph Min-Bisection, Densest Subgraph and Bipartite Clique
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
Machine Learning
MauveDB: supporting model-based user views in database systems
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Entity Resolution with Markov Logic
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Efficient inference with cardinality-based clique potentials
Proceedings of the 24th international conference on Machine learning
Bottom-up learning of Markov logic network structure
Proceedings of the 24th international conference on Machine learning
Efficient query evaluation on probabilistic databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Databases with uncertainty and lineage
The VLDB Journal — The International Journal on Very Large Data Bases
Automatically refining the wikipedia infobox ontology
Proceedings of the 17th international conference on World Wide Web
MCDB: a monte carlo approach to managing uncertain data
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Event queries on correlated probabilistic streams
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
BayesStore: managing large, uncertain data repositories with probabilistic graphical models
Proceedings of the VLDB Endowment
Fast and Simple Relational Processing of Uncertain Data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Online Filtering, Smoothing and Probabilistic Modeling of Streaming data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Collective semantic role labelling with Markov logic
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Towards efficient sampling: exploiting random walk strategies
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Sound and efficient inference with probabilistic and deterministic dependencies
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Memory-efficient inference in relational domains
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Joint inference in information extraction
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
A general method for reducing the complexity of relational inference and its application to MCMC
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Lifted first-order belief propagation
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
PrDB: managing and exploiting rich correlations in probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Markov Logic: An Interface Layer for Artificial Intelligence
Markov Logic: An Interface Layer for Artificial Intelligence
Speeding up inference in statistical relational learning by clustering similar query literals
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Tuffy: scaling up statistical inference in Markov logic networks using an RDBMS
Proceedings of the VLDB Endowment
Discriminative probabilistic models for relational data
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
New advances in inference by recursive conditioning
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Tuffy: scaling up statistical inference in Markov logic networks using an RDBMS
Proceedings of the VLDB Endowment
Program analysis and machine learning: a win-win deal
SAS'11 Proceedings of the 18th international conference on Static analysis
Interactive reasoning in uncertain RDF knowledge bases
Proceedings of the 20th ACM international conference on Information and knowledge management
Program analysis and machine learning: a win-win deal
APLAS'11 Proceedings of the 9th Asian conference on Programming Languages and Systems
Probabilistic databases with MarkoViews
Proceedings of the VLDB Endowment
Recognizing Inference in Texts with Markov Logic Networks
ACM Transactions on Asian Language Information Processing (TALIP) - Special Issue on RITE
AKBC-WEKEX '12 Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction
Discovering logical knowledge for deep question answering
Proceedings of the 21st ACM international conference on Information and knowledge management
Hazy: Making it Easier to Build and Maintain Big-data Analytics
Queue - Web Development
Probabilistic inference of object identifications for event stream analytics
Proceedings of the 16th International Conference on Extending Database Technology
A performance comparison of parallel DBMSs and MapReduce on large-scale text analytics
Proceedings of the 16th International Conference on Extending Database Technology
GeoDeepDive: statistical inference using familiar data-processing languages
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Towards high-throughput gibbs sampling at scale: a study across storage managers
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Knowledge harvesting in the big-data era
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Programming with personalized pagerank: a locally groundable first-order probabilistic logic
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
A Markov logic framework for recognizing complex events from multimodal data
Proceedings of the 15th ACM on International conference on multimodal interaction
Combining relational learning with SMT solvers using CEGAR
CAV'13 Proceedings of the 25th international conference on Computer Aided Verification
Statistical relational data integration for information extraction
RW'13 Proceedings of the 9th international conference on Reasoning Web: semantic technologies for intelligent data access
Symbolic optimization with SMT solvers
Proceedings of the 41st ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages
A temporal-probabilistic database model for information extraction
Proceedings of the VLDB Endowment
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Markov Logic Networks (MLNs) have emerged as a powerful framework that combines statistical and logical reasoning; they have been applied to many data intensive problems including information extraction, entity resolution, and text mining. Current implementations of MLNs do not scale to large real-world data sets, which is preventing their widespread adoption. We present Tuffy that achieves scalability via three novel contributions: (1) a bottom-up approach to grounding that allows us to leverage the full power of the relational optimizer, (2) a novel hybrid architecture that allows us to perform AI-style local search efficiently using an RDBMS, and (3) a theoretical insight that shows when one can (exponentially) improve the efficiency of stochastic local search. We leverage (3) to build novel partitioning, loading, and parallel algorithms. We show that our approach outperforms state-of-the-art implementations in both quality and speed on several publicly available datasets.