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Learning Probabilistic Relational Models (1999)  (Make Corrections)  (103 citations)
Nir Friedman, Lise Getoor, Daphne Koller, Avi Pfeffer
IJCAI



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Abstract: 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... (Update)

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BibTeX entry:   (Update)

L. Getoor, N. Friedman, D. Koller, and A. Pfeffer. Learning probabilistic relational models. In IJCAI '99. 1999. http://citeseer.ist.psu.edu/friedman99learning.html   More

@inproceedings{ friedman99learning,
    author = "Nir Friedman and Lise Getoor and Daphne Koller and Avi Pfeffer",
    title = "Learning Probabilistic Relational Models",
    booktitle = "{IJCAI}",
    pages = "1300-1309",
    year = "1999",
    url = "citeseer.ist.psu.edu/friedman99learning.html" }
Citations (may not include all citations):
351   Learning Bayesian networks: The combination of knowledge and.. - Heckerman, Geiger et al. - 1995  DBLP
219   A tutorial on learning with Bayesian networks - Heckerman - 1998
212   Inductive Logic Programming: Techniques and Applications (context) - Lavrac, Dzeroski - 1994
181   Optimal Statistical Decisions (context) - DeGroot - 1970
149   Learning to extract symbolic knowledge from the world wide w.. - Craven, DiPasquo et al. - 1998  ACM   DBLP
138   Probabilistic Horn abduction and Bayesian networks - Poole - 1993  ACM   DBLP
46   Probabilistic frame-based systems - Koller, Pfeffer - 1998  ACM   DBLP
39   Learning Bayesian networks is NP-complete - Chickering - 1996
35   From knowledge bases to decision models (context) - Wellman, Breese et al. - 1992
33   Learning belief networks in the presence of missing values a.. - Friedman - 1997  ACM   DBLP
28   Answering queries from contextsensitive probabilistic knowle.. - Ngo, Haddawy - 1996
17   sparse candidate (context) - Friedman, Nachman et al. - 1999
12   Learning probabilities for noisy firstorder rules - Koller, Pfeffer - 1997



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