Download Semantics in Adaptive and Personalized Services: Methods, by Manolis Wallace, Ioannis E. Anagnostopoulos, Phivos Mylonas, PDF

By Manolis Wallace, Ioannis E. Anagnostopoulos, Phivos Mylonas, Mária Bieliková

Semantics in Adaptive and customized prone, at the beginning moves one as a selected and maybe slender area. but, a more in-depth exam of the time period finds even more. On one hand there's the difficulty of semantics. these days, this as a rule refers back to the use of OWL, RDF or another XML established ontology description language which will symbolize the entities of challenge. nonetheless, semantics can also rather well seek advice from the distinction of the meanings and ideas, instead of mathematics measures, whatever the illustration used. nevertheless, there's the problem of edition, i.e. computerized re-configuration in keeping with a few context. this is able to be the community and equipment context, the appliance context or the consumer context; we check with the latter case as personalization. From a distinct point of view, there's the problem of the viewpoint from which to ascertain the subject. there's the perspective of instruments, touching on the algorithms and software program instruments you will use, the viewpoint of the tools, relating the summary methodologies and top practices you can still keep on with, in addition to the perspective of functions, touching on profitable and pioneering case reviews that paved the way in learn and innovation. Or a minimum of so we thought.

Based at the above reasoning, the editors pointed out key researchers and practitioners in all of the aforementioned different types and invited them to give a contribution a corresponding paintings to this e-book. even though, because the authors’ contributions began to arrive, the editors additionally began to notice that even if those different types perform each one bankruptcy to various levels, none of them can ever be absolutely out of date from them. furthermore, apparently thought and techniques are inherent within the improvement of instruments and purposes and inversely the applying can be inherent within the motivation and presentation of instruments and methods.

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Extra resources for Semantics in Adaptive and Personalized Services: Methods, Tools and Applications

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Fig. 2 Mobile TV recommender architecture. g. g. [14]). The content-based algorithms look at the ‘similarity’ between the user (profile) and the item (metadata) to recommend, while the collaborative filtering algorithms recommend the item if it has been appreciated by ‘similar’ users (based on consumption history or ratings). However, in the scope of the current work and to fit the needs of the recommending service, only the content-based approach is used by the profiling service. Therefore, the profiling service also relies on content metadata describing the semantics of the consumed contents and services.

In the content database, two westerns are present among others: “Unforgiven” and “Il buono, il bruto, il cattivo”. Except for the language, which would have been a discriminating factor, these ones are given a low matching value because of the Ontology-Based Profiling and Recommendations for Mobile TV 45 Fig. 11 Use Case 2. user’s non-interest. For the second one, Clint Eastwood is actor of the film, not director. Thus the movie is still considered not being relevant. The interesting case is the one of “Million dollar baby”, which is directed by Clint Eastwood and is about boxing.

2 Resource and Content Matching For resources, Mres = MSI(resI, C) is a function of resI and of all resources res(C) describing C. This similarity function represents proximity in the domain the resources belongs to: how much two entities of a same kind are similar? As content descriptions are all stored in a same knowledge base, RDF triples concerning each content must first be retrieved in order to be compared with resI. 7) (r = c) ∨ ∃t = ( s, p, o) ∈ KB : ( s ∈ res C ) ∧ (o = r ) ∧ ( p ∈ DOM ) where t is an RDF triple having for subject s, predicate p and object o and belonging to the knowledge base KB containing the content descriptions; c denotes the instance of content C in KB and DOM is the set of properties defined in the application domain (here, in our set of ontologies).

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