Summarizing significant subgraphs by probabilistic logic programming-Reference-Cited by-同舟云学术

Summarizing significant subgraphs by probabilistic logic programming

Published:2019-11-08 Issue:6 Volume:23 Page:1299-1312
ISSN:1088-467X
Container-title:Intelligent Data Analysis
language:
Short-container-title:IDA

Author:

Bellodi Elena¹,Satoh Ken²,Sugiyama Mahito²³

Affiliation:

1. Department of Engineering, University of Ferrara, Ferrara, Italy

2. National Institute of Informatics, Tokyo, Japan

3. JST, PRESTO

Publisher

IOS Press

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Theoretical Computer Science

Reference42 articles.

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3. R. Agrawal and R. Srikant, Fast algorithms for mining association rules, In Proceedings of the 20th International Conference on Very Large Data Bases, 1994, pp. 487–499.

4. Expectation Maximization over Binary Decision Diagrams for probabilistic logic programs;Bellodi;Intelligent Data Analysis,2013

5. Structure learning of probabilistic logic programs by searching the clause space;Bellodi;Theory and Practice of Logic Programming,2015

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