Download Journal on Data Semantics V by Miren I. Bagüés, Jesús Bermúdez, Arantza Illarramendi, PDF

By Miren I. Bagüés, Jesús Bermúdez, Arantza Illarramendi, Alberto Tablado, Alfredo Goñi (auth.), Stefano Spaccapietra, Paolo Atzeni, Wesley W. Chu, Tiziana Catarci, Katia P. Sycara (eds.)

The LNCS magazine on info Semantics is dedicated to the presentation of impressive paintings that, in a single method or one other, addresses study and improvement on matters concerning information semantics. in keeping with the hugely seen booklet platform Lecture Notes in machine technological know-how, this new magazine is largely disseminated and on hand worldwide.

The scope of the magazine levels from theories assisting the formal definition of semantic content material to leading edge domain-specific purposes of semantic wisdom. The magazine addresses researchers and complicated practitioners engaged on the semantic net, interoperability, cellular info prone, info warehousing, wisdom illustration and reasoning, conceptual database modeling, ontologies, and synthetic intelligence.

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We want to finish this section noticing one relationship that we have found between the two mentioned perspectives tackling the semantic interoperability issue in the introduction. In [1] the authors of the cream system, that consider the data integration perspective, define 12 different message types for a semantic mediator communication protocol, namely ask-all, ask-if, deliver, detect, generate, locate, reconcile, reply-all, reply-if, report, resolve-if and tell. The protocol contains message types for encapsulating all basic communication events they might need.

The same-as relation denotes that c and c are equivalent, while the kind-of and part-of relations denote that c and c are related by a specialization relation and a composition relation, respectively. Finally, the associates relation denotes that c and c are related by a generic positive semantic association. In Figure 1, examples of how OWL constructs are mapped on such semantic relations are given. Like linguistic features, also contextual features are weighted in H-Match. In particular, we associate a weight Wsp to strong properties, and a weight Wwp to weak properties, with Wsp ≥ Wwp to capture the different importance each kind of property has in characterizing the concept.

The term affinity function A(t, t ) → [0, 1] evaluates the affinity between two terms t and t based on the thesaurus. The term affinity function is borrowed from Artemis and it is reported here for the sake of clarity. A(t, t ) of two terms t and t is equal to the value of the highest-strength path of terminological relationships between them in T h if at least one path exists, and is zero otherwise. k {Wt→ni t } if k ≥ 1 0 otherwise (1) where: k is the number of paths between t and t in T h; t →ni t denotes the ith path of length n ≥ 1; Wt→ni t = W1tr · W2tr · .

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