This paper presents an overview of the research on learning statistical models from relational data being carried out at the University of Washington. Our work falls into five main directions: learning models of social networks; learning models of sequential relational processes; scaling up statistical relational learning to massive data sources; learning for knowledge integration; and learning programs in procedural languages. We describe some of the common themes and research issues arising from this work. 1
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277
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Learning probabilistic relational models
– Friedman, Getoor, et al.
- 1999
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234
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Enhanced hypertext categorization using hyperlinks
– Chakrabarti, Dom, et al.
- 1998
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223
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Reconciling schemas of disparate data sources: A machine-learning approach,” SIGMOD
– Doan, Domingos, et al.
- 2001
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179
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A.: Learning to Map between Ontologies on the Semantic Web
– Doan, Madhavan, et al.
- 2002
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161
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Mining high-speed data streams
– Domingos, Hulten
- 2000
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148
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Improving Text Classification by Shrinkage in a Hierarchy of Classes
– McCallum, Rosenfeld, et al.
- 1998
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146
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Probabilistic independence networks for hidden markov probability models
– Smyth, Heckerman, et al.
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98
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Adaptive Web sites: an AI challenge
– Perkowitz, Etzioni
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93
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The Intelligent Surfer: Probabilistic combination of link and content information in PageRank
– Richardson, Domingos
- 2002
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83
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Mining the network value of customers
– RICHARDSON, P
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76
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Symbolic dynamic programming for first-order MDPs
– Boutilier, Reiter, et al.
- 2001
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64
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Answering queries from contextsensitive probabilistic knowledge bases
– Ngo, Haddawy
- 1996
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63
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Bayesian Logic Programs
– Kersting, Raedt
- 2001
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62
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Relational Markov Models and their Application to Adaptive Web Navigation
– Anderson, Domingos, et al.
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48
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Rao-Blackwellised particle filtering for dynamic Bayesian networks. in Sequential Monte Carlo Methods in Practice, A. Doucet, et al Eds
– Murphy, Russell
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47
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Inductive logic programming and knowledge discovery
– Dzeroski
- 1996
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45
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Linkage and autocorrelation cause feature selection bias in relational learning
– Jensen, Neville
- 2002
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45
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Mining knowledge-sharing sites for viral marketing
– Richardson, Domingos
- 2002
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42
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Learning to match the schemas of data sources: A multistrategy approach
– Doan, Domingos, et al.
- 2003
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36
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Adaptive Web navigation for wireless devices
– ANDERSON, DOMINGOS, et al.
- 2001
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30
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Learning probabilities for noisy firstorder rules
– Koller, Pfeffer
- 1997
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26
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Dynamic probabilistic relational models
– Sanghai, Domingos, et al.
- 2003
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20
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Mining complex models from arbitrarily large databases in constant time
– Hulten, Domingos
- 2002
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20
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Building large knowledge bases by mass collaboration
– Richardson, Domingos
- 2003
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19
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Structured representation of complex stochastic systems
– Friedman, Koller, et al.
- 1998
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17
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Raedt. Towards discovering structural signatures of protein folds based on logical hidden markov models
– Kersting, Raiko, et al.
- 2003
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15
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Programming by demonstration using version space algebra
– Lau, Wolfman, et al.
- 2003
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12
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Foundations of assisted cognition systems
– Kautz, Etzioni, et al.
- 2003
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10
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Learning programs from traces using version space algebra
– Lau, Domingos, et al.
- 2003
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9
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Autocorrelation and linkage cause bias in evaluation of relational learners
– Jensen, Neville
- 2002
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9
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Learning with knowledge from multiple experts
– Richardson, Domingos
- 2003
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7
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Solving relational MDPs with first-order machine learning
– Mausam, Weld
- 2003
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4
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Building the Semantic Web by mass collaboration
– Richardson, Aggrawal, et al.
- 2003
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3
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Mining massive relational databases
– Hulten, Domingos, et al.
- 2003
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2
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Inductive policy selection for first-order Markov decision processes
– Yoon, Fern, et al.
- 2002
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1
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Learning complex semantic mappings between structured representations
– Doan, Domingos, et al.
- 2003
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