CORA

Complex Objects Ranking Algorithm

LACAM @ Dipartimento di Informatica - Università degli Studi di Bari - Via Orabona, 4 -70126 Bari

A short description
The distribution package
Related publications
Project team
FAQs

A short description

CORA is a probabilistic relational data mining method. It discovers relational preference patterns which determine when a complex object A precedes (in preference) another object B and then it uses these preference patterns to estimate the probability of the preference relation for any pair of complex objects. This probability is finally used to rank the objects. The probability is computed by extending the naive Bayes assumption to relational representations.
CORA is used to the domain of document image understanding for reading order detection and for document summarization.

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The distribution package

CORA is provided as a .jar file and can be executed on every machine with a JVM (1.5.0 or higher) installed.

Read the (readme.txt file for the installation)
Download the distribution package with datataset examples (CORA.zip)

Warning: The system CORA is free for evaluation, research and teaching purposes, but not for commercial purposes.
Please Acknowledge

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Project team

Project Leader

Michelangelo Ceci

Current Staff

Related publications

M.Ceci, A. Appice, C. Loglisci, & Donato Malerba. Complex objects ranking: a relational data mining approach. In S. Y. Shin, S. Ossowski, M. Schumacher, M. J. Palakal, and C.C. Hung, editors, SAC, pages 1071–1077. ACM, 2010.

M. Ceci, A. Appice, L. Macchia & D. Malerba. Relational Classification based on Emerging Patterns. Atti del XVI Convegno Nazionale su Sistemi Evoluti per Basi di Dati, SEBD 2008. 21-25 Giugno, Mondello (Palermo) 2008. 45-56

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FAQs

None yet available.
Send all requests/comments to: Michelangelo Ceci Dipartimento di Informatica, Università degli Studi di Bari (Italy).

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