Search results for " recommender systems"

showing 5 items of 5 documents

Semantic technologies for industry: From knowledge modeling and integration to intelligent applications

2013

Artificial Intelligence technologies are growingly used within several software systems ranging from Web services to mobile applications. It is by no doubt true that the more AI algorithms and methods are used the more they tend to depart from a pure "AI" spirit and end to refer to the sphere of standard software. In a sense, AI seems strongly connected with ideas, methods and tools that are not (yet) used by the general public. On the contrary, a more realistic view of it would be a rich and pervading set of successful paradigms and approaches. Industry is currently perceiving semantic technologies as a key contribution of AI to innovation. In this paper a survey of current industrial expe…

Computer scienceKnowledge RepresentationRecommender systemcomputer.software_genreNLPIndustrial ApplicationsWorld Wide WebKnowledge modelingSemantic TechnologiesArtificial Intelligencesemantic searchontologiesKnowledge Representation; Semantic Technologies; Industrial Applicationsinformation retrievalSoftware systembusiness.industrySemantic searchSketchBPMSemantic technologyApplications of artificial intelligenceNLP information retrieval semantic search recommender systems ontologies BPMrecommender systemsWeb servicebusinesscomputerIntelligenza Artificiale
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Tīmekļa vietņu un interneta veikalu personalizēšanas iespējas, problēmas un risinājumi

2015

Maģistra darbs ir veltīts tīmekļa vietņu un interneta veikalu personalizēšanai, tas ir, satura pielāgošana lietotājiem un produktu rekomendācijas. Darbā ir apskatīta personalizēšanas teorija un rekomendāciju algoritmi, salīdzināti populārākie satura personalizēšanas servisi un veikta produktu rekomendāciju servisu analīze. Autors cenšas atrisināt rekomendācijas algoritma pielietošanas problēmu interneta veikalā un piedāvā iespējamo risinājumu. Beigās tiek salīdzināts piedāvātais risinājums ar pieejamiem servisiem.

produktu rekomendāciju sistēmasDatorzinātneweb personalizationvietņu personalizēšanaproduct recommender systemse-komercija
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A Context-Aware Mobile Solution for Assisting Tourists in a Smart Environment

2017

Computer sciencebusiness.industryInternet privacyRecommender Systems020206 networking & telecommunicationsContext (language use)02 engineering and technologyRecommender systemContext Awareness; E-Tourism; Recommender SystemsE-Tourism020204 information systemsAdaptive system0202 electrical engineering electronic engineering information engineeringContext awarenessSmart environmentbusinessContext AwarenessProceedings of the 50th Hawaii International Conference on System Sciences (2017)
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The contribution of AI to enhance understanding of Cultural Heritage.

2013

The Artificial Intelligence & Cultural Heritage (AI & CH) working group was born in 1999 with the aim at promoting various scientific activities to increase a more active collaboration between the sectors of cultural assets and artificial intelligence. The many events (workshops and schools) organized over the years have shown the validity of this group for exchanging ideas and gathering researchers and practitioners from different fields. New applications of informatics and artificial intelligence have provided the opportunity to produce innovative tools for documenting, managing and communicating cultural heritage. For this anniversary we intend to show how some of the most important meth…

roboticsSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniKnowledge managementbusiness.industryComputer scienceIntelligent user interfaces ontology recommender systems robotics virtual archaeologyRoboticsRecommender systemOntology (information science)Intelligent user interfacesCultural heritageArtificial Intelligencevirtual archaeologyontologyArtificial intelligencerecommender systemsbusiness
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A Hybrid Recommender System for Cultural Heritage Promotion

2021

Assisting users during their cultural trips is paramount in promoting the heritage of a territory. Recommender Systems offer the automatic tools to guide users in their decision process, by maximizing the adherence of the proposed contents with the particular preferences of every single user. However, traditional recommendation paradigms suffer from several drawbacks which are exacerbated in Cultural Heritage scenarios, due to the extremely wide range of users behaviors, which may also depend on their different educational backgrounds. In this paper, we propose a Hybrid recommender system which combines the four most common recommendation paradigms, namely collaborative filtering, popularit…

Cultural heritageWorld Wide WebSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniPromotion (rank)Computer sciencemedia_common.quotation_subjectCollaborative filteringTRIPS architectureRecommender systemDecision processCultural heritage Recommender systemsPopularitymedia_common
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