Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Proceedings of the 11th international conference on World Wide Web
ECML '93 Proceedings of the European Conference on Machine Learning
Machine Learning
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Espresso: leveraging generic patterns for automatically harvesting semantic relations
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Semantic taxonomy induction from heterogenous evidence
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Scaling textual inference to the web
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Learning graph walk based similarity measures for parsed text
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
TextRunner: open information extraction on the web
NAACL-Demonstrations '07 Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations
Open information extraction from the web
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Unsupervised named-entity extraction from the Web: An experimental study
Artificial Intelligence
Fast query execution for retrieval models based on path-constrained random walks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning relations by pathfinding
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
FactRank: random walks on a web of facts
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Collective intelligence as a source for machine learning self-supervision
Proceedings of the 4th International Workshop on Web Intelligence & Communities
Reading the web with learned syntactic-semantic inference rules
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Towards distributed MCMC inference in probabilistic knowledge bases
AKBC-WEKEX '12 Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction
Transforming Wikipedia into a large scale multilingual concept network
Artificial Intelligence
Modeling online creative collaborations
XRDS: Crossroads, The ACM Magazine for Students - Creativity + Computer Science
Knowledge harvesting in the big-data era
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Let's get together: the formation and success of online creative collaborations
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Autonomously reviewing and validating the knowledge base of a never-ending learning system
Proceedings of the 22nd international conference on World Wide Web companion
Mining frequent neighborhood patterns in a large labeled graph
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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 study of the knowledge base requirements for passing an elementary science test
Proceedings of the 2013 workshop on Automated knowledge base construction
Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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We consider the problem of performing learning and inference in a large scale knowledge base containing imperfect knowledge with incomplete coverage. We show that a soft inference procedure based on a combination of constrained, weighted, random walks through the knowledge base graph can be used to reliably infer new beliefs for the knowledge base. More specifically, we show that the system can learn to infer different target relations by tuning the weights associated with random walks that follow different paths through the graph, using a version of the Path Ranking Algorithm (Lao and Cohen, 2010b). We apply this approach to a knowledge base of approximately 500,000 beliefs extracted imperfectly from the web by NELL, a never-ending language learner (Carlson et al., 2010). This new system improves significantly over NELL's earlier Horn-clause learning and inference method: it obtains nearly double the precision at rank 100, and the new learning method is also applicable to many more inference tasks.