486,950 research outputs found

    Recommendations based on social links

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    The goal of this chapter is to give an overview of recent works on the development of social link-based recommender systems and to offer insights on related issues, as well as future directions for research. Among several kinds of social recommendations, this chapter focuses on recommendations, which are based on users’ self-defined (i.e., explicit) social links and suggest items, rather than people of interest. The chapter starts by reviewing the needs for social link-based recommendations and studies that explain the viability of social networks as useful information sources. Following that, the core part of the chapter dissects and examines modern research on social link-based recommendations along several dimensions. It concludes with a discussion of several important issues and future directions for social link-based recommendation research

    A Personalised Ranking Framework with Multiple Sampling Criteria for Venue Recommendation

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    Recommending a ranked list of interesting venues to users based on their preferences has become a key functionality in Location-Based Social Networks (LBSNs) such as Yelp and Gowalla. Bayesian Personalised Ranking (BPR) is a popular pairwise recommendation technique that is used to generate the ranked list of venues of interest to a user, by leveraging the user's implicit feedback such as their check-ins as instances of positive feedback, while randomly sampling other venues as negative instances. To alleviate the sparsity that affects the usefulness of recommendations by BPR for users with few check-ins, various approaches have been proposed in the literature to incorporate additional sources of information such as the social links between users, the textual content of comments, as well as the geographical location of the venues. However, such approaches can only readily leverage one source of additional information for negative sampling. Instead, we propose a novel Personalised Ranking Framework with Multiple sampling Criteria (PRFMC) that leverages both geographical influence and social correlation to enhance the effectiveness of BPR. In particular, we apply a multi-centre Gaussian model and a power-law distribution method, to capture geographical influence and social correlation when sampling negative venues, respectively. Finally, we conduct comprehensive experiments using three large-scale datasets from the Yelp, Gowalla and Brightkite LBSNs. The experimental results demonstrate the effectiveness of fusing both geographical influence and social correlation in our proposed PRFMC framework and its superiority in comparison to BPR-based and other similar ranking approaches. Indeed, our PRFMC approach attains a 37% improvement in MRR over a recently proposed approach that identifies negative venues only from social links

    Municipal transitions: The social, energy, and spatial dynamics of sociotechnical change in South Tyrol, Italy

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    With the aim of proposing recommendations on how to use social and territorial specificities as levers for wider achievement of climate and energy targets at local level, this research analyses territories as sociotechnical systems. Defining the territory as a sociotechnical system allows us to underline the interrelations between space, energy and society. Groups of municipalities in a region can be identified with respect to their potential production of renewable energy by means of well-known data-mining approaches. Similar municipalities linking together can share ideas and promote collaborations, supporting clever social planning in the transition towards a new energy system. The methodology is applied to the South Tyrol case study (Italy). Results show eight different spatially-based sociotechnical systems within the coherent cultural and institutional context of South Tyrol. In particular, this paper observes eight different systems in terms of (1) different renewable energy source preferences in semi-urban and rural contexts; (2) different links with other local planning, management, and policy needs; (3) different socio-demographic specificities of individuals and families; (4) presence of different kinds of stakeholders or of (5) different socio-spatial organizations based on land cover. Each energy system has its own specificities and potentialities, including social and spatial dimensions, that can address a more balanced, inclusive, equal, and accelerated energy transition at the local and translocal scale

    Enabling Mobile Communications for the Needy: Affordability Methodology, and Approaches to Requalify Universal Service Measures

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    This paper links communications and media usage to social and household economics boundaries. It highlights that in present day society, communications and media are a necessity, but not always affordable, and that they furthermore open up for addictive behaviors which raise additional financial and social risks. A simple and efficient methodology compatible with state-of-the-art social and communications business statistics is developed, which produces the residual communications and media affordability budget and ultimately the value-at-risk in terms of usage and tariffs. Sensitivity analysis provides precious information on bottom-up communications and media adoption on the basis of affordability. This approach differs from the regulated but often ineffective Universal service obligation, which instead of catering for individual needs mostly addresses macro-measures helping geographical access coverage (e.g. in rural areas). It is proposed to requalify the Universal service obligations on operators into concrete measures, allowing, with unchanged funding, the needy to adopt mobile services based on their affordability constraints by bridging the gap to a standard tariff. Case data are surveyed from various countries. ICT policy recommendations are made to support widespread and socially responsible communications access.Affordability, Mobile communications, Media usage, Addiction, Residual budget, Social and communications regulations, Social tariffs

    Generic knowledge-based analysis of social media for recommendations

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    Recommender systems have been around for decades to help people find the best matching item in a pre-defined item set. Knowledge-based recommender systems are used to match users based on information that links the two, but they often focus on a single, specific application, such as movies to watch or music to listen to. In this presentation, we present our Interest-Based Recommender System (IBRS). This knowledge-based recommender system provides recommendations that are generic in three dimensions: IBRS is (1) domain-independent, (2) language-independent, and (3) independent of the used social medium. To match user interests with items, the first are derived from the user's social media profile, enriched with a deeper semantic embedding obtained from the generic knowledge base DBpedia. These interests are used to extract personalized recommendations from a tagged item set from any domain, in any language. We also present the results of a validation of IBRS by a test user group of 44 people using two item sets from separate domains: greeting cards and holiday homes

    The interaction between social capital, creativity and efficiency in organizations

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    Some have argued social capital provides synergy for creative cooperation among employees. Creativity and efficiency have been established as two concepts that oppose each other; however, they are both essential to maintain the competitiveness of an organization. This study investigated the interaction between social capital on organizational creativity and efficiency and examined the links between organizational creativity and efficiency. In addition, it is aimed to provide recommendations based on results regarding the effectiveness of social capital on organizational creativity. In this empirical study, the data on perceptions concerning social capital, organizational creativity and organizational efficiency was gathered by means of a questionnaire completed by 131 managers working in the Turkish Employment Agency. Subsequently, data was analyzed with the SmartPLS software and presented in tables. The findings showed that social capital has an effect on organizational creativity and organizational efficiency. Results also provided support for the effect of organizational creativity on the organizational efficiency
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