@inproceedings{pub5101,
    abstract = {We present an intelligent service matchmaker, called iSeM, for adaptive and hybrid semantic service selection that exploits the full semantic profile in terms of signature annotations in description logic ${\mathcal SH}$ and functional specifications in SWRL. In particular, iSeM complements its strict logical signature matching with approximated reasoning based on logical concept abduction and contraction together with information-theoretic similarity and evidential coherence-based valuation of the result, and non-logic-based approximated matching. Besides, it may avoid failures of signature matching only through logical specification plug-in matching of service preconditions and effects. Eventually, it learns the optimal aggregation of its logical and non-logic-based matching filters off-line by means of binary SVM-based service relevance classifier with ranking. We demonstrate the usefulness of iSeM by example and preliminary results of experimental performance evaluation. },
    year = {2010},
    title = {iSeM: Approximated Reasoning for Adaptive Hybrid Selection of Semantic Services},
    booktitle = {Proceedings of the 4th IEEE International Conference on Semantic Computing. IEEE International Conference on Semantic Computing (ICSC-2010), 4th, September 22-24, Pittsburgh,, PA, United States},
    publisher = {Springer-Verlag},
    author = {Matthias Klusch and Patrick Kapahnke}
}