Learning Probabilistic Relational Models Export

@article{citeulike:453442, abstract = {Most real-world data is stored in relational form. In contrast, most statistical learning methods, e.g., Bayesian network learning, work only with \"flat\" data representations, forcing us to convert our data into a form that loses much of the relational structure. The recently introduced framework of probabilistic relational models (PRMs) allow us to represent much richer dependency structures, involving multiple entities and the relations between them; they allow the properties of an...}, author = {Getoor, Lise}, citeulike-article-id = {453442}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.32.4994}, journal = {Lecture Notes in Computer Science}, keywords = {prm}, pages = {322--??}, posted-at = {2007-11-08 13:45:13}, priority = {2}, title = {Learning Probabilistic Relational Models}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.32.4994}, volume = {1864}, year = {2000} }

TY - JOUR ID - citeulike:453442 L3 - citeulike-article-id:453442 N2 - Most real-world data is stored in relational form. In contrast, most statistical learning methods, e.g., Bayesian network learning, work only with "flat" data representations, forcing us to convert our data into a form that loses much of the relational structure. The recently introduced framework of probabilistic relational models (PRMs) allow us to represent much richer dependency structures, involving multiple entities and the relations between them; they allow the properties of an... JF - Lecture Notes in Computer Science EP - ?? TI - Learning Probabilistic Relational Models VL - 1864 SP - 322 KW - prm AU - Getoor, Lise PY - 2000/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.32.4994 ER -