Data Integration: The Relational Logic Approach by Michael Genesereth, Thomas Dietterich, Ronald Brachman

By Michael Genesereth, Thomas Dietterich, Ronald Brachman

Information integration is a severe challenge in our more and more interconnected yet unavoidably heterogeneous global. there are various information resources to be had in organizational databases and on public info structures just like the world-wide-web. now not unusually, the assets usually use diversified vocabularies and diverse information buildings, being created, as they're, by means of assorted humans, at diverse occasions, for various reasons. The aim of knowledge integration is to supply programmatic and human clients with built-in entry to a number of, heterogeneous information assets, giving every one person the appearance of a unmarried, homogeneous database designed for their particular want. the excellent news is that, in lots of circumstances, the knowledge integration procedure might be computerized. This ebook is an creation to the matter of knowledge integration and a rigorous account of 1 of the top ways to fixing this challenge, viz., the relational good judgment technique. Relational good judgment offers a theoretical framework for discussing information integration. in addition, in lots of very important circumstances, it presents algorithms for fixing the matter in a computationally useful approach. in lots of respects, relational common sense does for facts integration what relational algebra did for database idea a number of many years in the past. A spouse website offers interactive demonstrations of the algorithms. desk of Contents: Preface / Interactive variation / advent / simple options / question Folding / question making plans / grasp Schema administration / Appendix / References / Index / writer Biography

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The second relation contains similar information for United Airlines (ua). The third relation is the set of every triple consisting of an airline and cities that are connected by flights offered by that airline via exactly one stopover. There is a single ternary base relation flight, which stores triples of airline, origin, and destination for all nonstop flights. For example, flight(sw,tus,sfo) means that Southwest Airlines offers a nonstop flight from Tucson to San Francisco. Using this base relation, we can define the source relations as shown below.

Cm be new constants. A conjunction of inequalities φ in– – volving only c1, . . , cm and the constants in X 1, . . , X n is called an attribute constraint. A conjunctive rule ri satisfies an attribute constraint φ if and only if all inequalities in φ hold after replacing each cj – in φ by the corresponding X i[ j ]. If rules ri1, . . , rik are truly disjunctive with most general witness Z – – and there is an attribute constraint φ satisfied by X 1, . . , X n but not satisfied by any Xj with j∈{1, .

For example, the plan shown below outputs yes exactly when the input graph contains G1 as a subgraph and when the vertices are colored with at most three colors. query(yes) :- v1(X1) & v1(X2) & v1(X3) & v1(Y) & v2(X1,X2) & v2(X2,X3) & v2(X3,X1) & v2(X1,Y) & v2(X2,Y) & v2(X3,Y) It follows that this query plan is contained in our query. More generally, every query plan that checks that the input graph contains a non-three-colorable subgraph and that all the vertices in the subgraph are colored by at most three colors is contained in this query plan.

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