In the task of modeling user preferences for movie recommender systems, recent research has demonstrated benefits describing movies with their eudaimonic and hedonic scores (E H scores), which reflect depth message level fun experience they provide, respectively. So far, labeling E been done manually using a dedicated instrument (a questionnaire), is time-consuming. To address this issue, we propose an automatic approach predicting scores. Specifically, collected 709 from 370 users (with...

This work discusses the ICT solutions designed and developed within OR.C.HE.S.T.R.A. Project. The mission of such an industrial experimental project (Organization Cultural Heritage Smart Tourism Real-time Accessibility) consists in developing some technological for tourists inhabitants aimed at appraising cultural heritage historic centre Naples. is based on a Social Innovation approach where services are created engaging all possible actors ecosystem oriented to Culture tourism (companies,...

Abstract Social choice aggregation strategies have been proposed as an explainable way to generate recommendations groups of users. However, it is not trivial determine the best strategy apply for a specific group. Previous work highlighted that performance group recommender system affected by internal diversity members’ preferences. few them empirically evaluated how distribution preferences in determines which most effective. Furthermore, only studies impact providing explanations...

In travel domains, decision support systems provide to tourists in the planning of their vacation. particular, when number possible Points Interest (POI) visit is large, system should help providing recommendations on POI that could be more interesting for them. Since traveling is, usually, an activity involves small groups people, take simultaneously into account preferences each group's member. At same time, it also model intra-group relationships, which can have impact group...

Recommendation systems based on collaborative filtering methods can be exploited in the context of providing personalized artworks tours within a museum. However, order to effectively used, several problems have addressed: user preferences are not expressed as rating, items suggested located physical space, and users may group. In this work, we present general framework that, by using Matrix Factorization (MF) approach graph representation museum, addresses problem generating then...

In an Internet of Things vision smarts museums, recommendation systems based on collaborative filtering approaches can be exploited in the context providing personalized artworks tours. this work, we address problem generating and then recommending sequence for a group visitors within museum. Differently from recommender system e-commerce application, problem, here, is trying to maximize satisfaction proposed recommendations, while taking into account items' ordering that satisfies each...

Media monitoring services allow their customers, mostly companies, to receive, on a daily basis, list of documents from mass media that discuss topics relevant the company. However, often generate these lists by using keyword-filtering techniques, which introduce many false positives. Hence, before end users, i.e., employees company, may consult and find documents, human editor must inspect keyword-filtered remove This is time consuming job. In this paper we present recommender system aims...

Recent studies on recommender systems raise attention to the importance of context, intended both as external environment and even user's internal state, such as, for example, mood in which users are going perform recommended activities. This is a key factor also group recommendation domain, where context characterized by presence other people with whom activities must be performed. In this case, social influences relationships between come into play, individual satisfaction that each user...

Powder metallurgy (PM) is the branch of that deals with design/production near-net-shaped sintered workpieces different shapes and characteristics. The produced are used in automotive, aviation, aerospace industries, just to name a few. quality largely depends on powder compaction techniques accurate adjustments process parameters. Currently, these parameters done manually thus resulting laborious time-intensive effort. To this end, article explores use machine learning (ML) proposes an...

Summary Recommendation systems based on collaborative filtering methods can be exploited in the context of providing personalized artworks tours within a museum. However, to effectively used, we have several problems addressed: user preferences are not expressed as rating and recommendation must provide for new users efficient simple elicitation processes that do require much effort time. In this work, present evaluate 2 state‐of‐the‐art approaches share aim rely individual item ratings. The...

Content-based recommender (CBR) systems take advantage of item characteristics and user propensities for these in order to select the items that are better suited a user. Related work has shown hedonia (pleasure) eudaimonia (deeper meaning) account preferences domain movies. However, labeling with hedonic/eudaimonic properties measuring propensity eudaimonic/hedonic experiences could be done only through questionnaires. In this we present results our work-in-progress on prediction eudaimonic...

Group Recommender Systems (GRSs), unlike recommendations for individuals, provide suggestions groups of people. Clearly, many activities are often experienced by a group rather than an individual (visiting restaurant, traveling, watching movie, etc.) hence the requirement such systems. The topic is gradually receiving more and attention, with increased number papers published at significant venues, which enabled predominance online social platforms that allow their users to interact in...

Personality accounts for how individuals differ in their enduring emotional, interpersonal, experiential, attitudinal and motivational styles. Personality, especially the form of Five Factor Model, has shown usefulness personalized systems, such as recommender systems. In this work, we focus on a personality model that is targeted at motivations multimedia consumption. The composed two dimensions: (i) eudaimonic orientation users (EO) (ii) hedonic (HO). While former much user interested...

Recent research has shown that explanations serve as an important means to increase transparency in group recommendations while also increasing users' privacy concerns. However, it is currently unclear what personal and contextual factors affect concerns about various types of information. This paper studies the effect personality traits preference scenarios ---having a majority or minority preference--- on their regarding location emotion To create natural decision-making where users can...