By Paul Groth, Elena Simperl, Alasdair Gray, Marta Sabou, Markus Krötzsch, Freddy Lecue, Fabian Flöck, Yolanda Gil

The two-volume set LNCS 9981 and 9982 constitutes the refereed lawsuits of the 15thInternational Semantic net convention, ISWC 2016, which used to be held in Kobe, Japan, in October 2016. The seventy five complete papers provided in those lawsuits have been rigorously reviewed and chosen from 326 submissions.
The foreign Semantic net convention is the most advantageous discussion board for Semantic net learn, the place leading edge clinical effects and technological ideas are offered, the place difficulties and strategies are mentioned, and the place the way forward for this imaginative and prescient is being constructed. It brings jointly experts in fields similar to man made intelligence, databases, social networks, dispensed computing, net engineering, details platforms, human-computer interplay, traditional language processing, and the social sciences.
The examine tune solicited novel and critical examine contributions addressing theoretical, analytical, empirical, and sensible facets of the Semantic internet. The functions tune solicited submissions exploring the advantages and demanding situations of utilizing semantic applied sciences in concrete, functional functions, in contexts starting from to executive and technological know-how. The newly brought assets tune sought submissions delivering a concise and transparent description of a source and its (expected) utilization. conventional assets comprise ontologies, vocabularies, datasets, benchmarks and replication experiences, providers and software program. along with extra proven kinds of assets, the song solicited submissions of recent sorts of assets resembling ontology layout styles, crowdsourcing activity designs, workflows, methodologies, and protocols and measures.

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Extra resources for The Semantic Web – ISWC 2016: 15th International Semantic Web Conference, Kobe, Japan, October 17–21, 2016, Proceedings, Part I

Sample text

4, which assimilate user-provided feedback as evidence that a given resource S is, or is not, an entity. For example, if "War and Peace" appears in a triple in the returned results as an instance of Movie, where Movie is confirmed by feedback to be an entity type, this adds strength to the belief that "War and Peace" is an instance of Entity in our metamodel. Weight Learning for PSL Program Generation. We generated two PSL programs P SL(S) and P SL(F) for inference by learning weights for the rules in S and F.

The theory behind these query languages is relational algebra or equivalently, relational calculus, formalisms that for sets have a clean and intuitive semantics for users, developers and theoreticians [1]. The same cannot be said of their extensions to multisets, whose theory is complex (particular containment of queries) and their practical use not always clear for users and developers [8]. Worst, there exist several possible ways of extending set relational operators to multisets and one can find them in practice.

The PSL weight learning process takes a PSL program (possibly with initial weights), a specification of both evidence and query predicates, and sample data. A predicate is said to be an evidence predicate if all its ground atoms have known truth values by observation. A predicate is said to be a query predicate if one or more of its ground atoms have unknown truth values. The process returns a relative non-negative weight for each rule. A positive weight denotes that a rule is supported by the sample data whereas the magnitude indicates the strength of that support.

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