A framework for relational link discovery

Authors:
Dan Luo;Chao Luo;Chunzhi Zhang
Affiliations:
Faculty of Information Technology, University of Technology Sydney, Australia;Faculty of Software, Liaoning Technical University, China;Beijing Vocational & Technical Institute of Industry, China
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

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Abstract

Link discovery is an emerging research direction for extracting evidences and links from multiple data sources. This paper proposes a self-organizing framework for discovering links from multi-relational databases. It includes main functional modules for developing adaptive data transformers and representation specification, multi-relational feature construction, and self-organizing multi-relational correlation and link discovery algorithms.