P2P case storage and retrieval with an unspecified ontology |
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Authors: | Shlomo Berkovsky Tsvi Kuflik Francesco Ricci |
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Affiliation: | (1) CSIRO, ICT Centre, Hobart, Australia;(2) Management Information Systems Department, University of Haifa, Haifa, Israel;(3) Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy |
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Abstract: | Traditional approaches for similarity-based retrieval of structured data, such as Case-Based Reasoning (CBR), have been largely
implemented using centralized storage systems. In such systems, when the cases contain both numeric and free-text attributes,
similarity-based retrieval cannot exploit standard speedup techniques based on multi-dimensional indexing, and the retrieval
is implemented by an exhaustive comparison of the case to be solved with the whole set of stored cases. In this work, we review
current research on Peer-to-Peer (P2P) and distributed CBR techniques and propose a novel approach for storage of the case-base
in a decentralized Peer-to-Peer environment using the notion of Unspecified Ontology to improve the performance of the case
retrieval stage and build CBR systems that can scale up to large case-bases. We develop an algorithm for efficient retrieval
of approximated most-similar cases, which exploits inherent characteristics of the unspecified ontology in order to improve
the performance of the case retrieval stage in the CBR problem solving cycle. The experiments show that the algorithm successfully
retrieves cases close to the most-similar cases, while reducing the number of cases to be compared. Hence, it improves the
performance of the retrieval stage. Moreover, the distributed nature of our approach eliminates the computational bottleneck
and single point of failure of the centralized storage systems. |
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Keywords: | Case-Based Reasoning Similarity-based retrieval Peer-to-Peer Unspecified ontology |
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