Heuristics for automated knowledge source integration and service composition

Authors:
Patrick N. Bless;Diego Klabjan;Soo Y. Chang
Affiliations:
Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA;Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA;Department of Industrial Engineering, Pohang University of Science and Technology, Hyoja San 31, Pohang, Republic of Korea
Venue:
Computers and Operations Research
Year:
2008

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Abstract

The NP-hard component set identification problem is a combinatorial problem arising in the context of knowledge discovery, information integration, and knowledge source/service composition. Considering a granular knowledge domain consisting of a large number of individual bits and pieces of domain knowledge (properties) and a large number of knowledge sources and services that provide mappings between sets of properties, the objective of the component set identification problem is to select a minimum cost combination of knowledge sources that can provide a joint mapping from a given set of initially available properties (initial knowledge) to a set of initially unknown properties (target knowledge). We provide a general framework for heuristics and consider construction heuristics that are followed by local improvement heuristics. Computational results are reported on randomly generated problem instances.