Packing Steiner trees: a cutting plane algorithm and computational results
Mathematical Programming: Series A and B
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
IEEE Transactions on Knowledge and Data Engineering
What Are Ontologies, and Why Do We Need Them?
IEEE Intelligent Systems
IEEE Intelligent Systems
Web Services: Been There, Done That?
IEEE Intelligent Systems
Rank Aggregation for Automatic Schema Matching
IEEE Transactions on Knowledge and Data Engineering
Heuristics for automated knowledge source integration and service composition
Computers and Operations Research
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We introduce a new combinatorial problem referred to as the component set identification problem, arising in the context of knowledge discovery, information integration, and knowledge source/service composition. The main motivation for studying this problem is the widespread proliferation of digital knowledge sources and services. 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 position the component set identification problem relative to other combinatorial problems and provide a classification scheme for the different variations of the problem. The problem is next modeled on a directed graph and analyzed in terms of its complexity. The directed graph representation is then augmented and transformed into a time-expanded network representation that is subsequently used to develop an exact solution procedure based on integer programming and branch-and-bound. We enhance the solver by developing preprocessing techniques. All findings are supported by computational experiments.