View Learning for Statistical Relational Learning: With an Application to Mammography
Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 677-682.
Abstract
Statistical relational learning (SRL) constructs probabilistic models from relational databases. A key capability of SRL is the learning of arcs (in the Bayes net sense) connecting entries in different rows of a relational table, or in different tables. Nevertheless, SRL approaches currently are constrained to use the existing database schema. For many database applications, users find it profitable to define alternative “views” of the database, in effect defining new fields or tables. Such new fields or tables can also be highly useful in learning. We provide SRL with the capability of learning new views.
@inproceedings{ijcai2005p62,
title = {View Learning for Statistical Relational Learning: With an Application to Mammography},
author = {Davis, Jesse and Burnside, Elizabeth S. and Dutra, Inês de Castro and Jr., C. David Page and Ramakrishnan, Raghu and Costa, Vítor Santos and Shavlik, Jude W.},
booktitle = {Proceedings of the Nineteenth International Joint Conference on
Artificial Intelligence, {IJCAI-05}},
publisher = {International Joint Conferences on Artificial Intelligence},
pages = {677--682},
year = {2005},
url = {https://ijcai.org/proceedings/2005/62},
}
TY - CPAPER TI - View Learning for Statistical Relational Learning: With an Application to Mammography AU - Davis, Jesse AU - Burnside, Elizabeth S. AU - Dutra, Inês de Castro AU - Jr., C. David Page AU - Ramakrishnan, Raghu AU - Costa, Vítor Santos AU - Shavlik, Jude W. T2 - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05 PB - International Joint Conferences on Artificial Intelligence PY - 2005 SP - 677 EP - 682 UR - https://ijcai.org/proceedings/2005/62 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
