View Learning for Statistical Relational Learning: With an Application to Mammography

• Type: Article in International Conference Proceedings Book
• Date: 2005

Authors

Davis, J (Author) Other; Burnside, E (Author) Other; Dutra, I (Author) Other; Page, D (Author) Other; Ramakrishnan, R (Author) Other; Costa, VS (Author) FCUP; Shavlik, J (Author) Other

Conference proceedings International

Title: IJCAI International Joint Conference on Artificial Intelligence

Pages: 677-683

19th International Joint Conference on Artificial Intelligence, IJCAI 2005

Edinburgh, 30 July 2005 through 5 August 2005

Indexing

ISI Web of Knowledge - 28 Citations

Scopus - 47 Citations

Other information

Authenticus ID: P-008-C7R

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7