Personalized Recommendation of Semantically Annotated Media Contents

Autor:	Beniamino Di Martino, Marco Scialdone, Salvatore Venticinque, Alba Amato
Přispěvatelé:	Vari, Amato, Alba, DI MARTINO, Beniamino, Marco, Scialdone, Venticinque, Salvatore
Rok vydání:	2014
Předmět:	World Wide Web Set (abstract data type) Focus (computing) Information retrieval Artificial Intelligence Computer science Discrete optimization Similarity (psychology) Vector space model Ontology (information science) Optimal decision Domain (software engineering)
Zdroj:	Studies in Computational Intelligence ISBN: 9783319015705 IDC
DOI:	10.1007/978-3-319-01571-2_31
Popis:	The optimal decision about the best set of recommendations to the user is a relevant problem in different application contexts. Here we focus on a methodology for dynamically and efficiently retrieval and delivery of multimedia contents, like documents, images, video etc., which have been annotated with semantic information. We introduce the definition and the computation of the similarity between sets of concepts belonging to a common ontology and discrete optimization technique for choosing the ones to be recommended.We enable personal agents reasoning about the best set of recommendations, which are relevant to the user’s profile, so optimizing his/her satisfaction. We present its implementation in a framework that supports experts in the domain of the Cultural Heritage to augment the archaeological site with a set of multimedia contents.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2749209a8c8381d548ceebad8d1b3e2a https://doi.org/10.1007/978-3-319-01571-2_31 Zobrazit plný text záznamu