Computer Science – Artificial Intelligence
Scientific paper
2007-04-24
Computer Science
Artificial Intelligence
To appear in Theory and Practice of Logic Programming (TPLP)
Scientific paper
This paper considers the problem of reasoning on massive amounts of (possibly distributed) data. Presently, existing proposals show some limitations: {\em (i)} the quantity of data that can be handled contemporarily is limited, due to the fact that reasoning is generally carried out in main-memory; {\em (ii)} the interaction with external (and independent) DBMSs is not trivial and, in several cases, not allowed at all; {\em (iii)} the efficiency of present implementations is still not sufficient for their utilization in complex reasoning tasks involving massive amounts of data. This paper provides a contribution in this setting; it presents a new system, called DLV$^{DB}$, which aims to solve these problems. Moreover, the paper reports the results of a thorough experimental analysis we have carried out for comparing our system with several state-of-the-art systems (both logic and databases) on some classical deductive problems; the other tested systems are: LDL++, XSB, Smodels and three top-level commercial DBMSs. DLV$^{DB}$ significantly outperforms even the commercial Database Systems on recursive queries. To appear in Theory and Practice of Logic Programming (TPLP)
Leone Nicola
Lio Vincenzino
Panetta Claudio
Terracina Giorgio
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