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  •   Bozen-Bolzano Institutional Archive (BIA)
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    Visual Analysis of Recommendation Performance 

    Çoba L; Symeonidis P; Zanker M (ACM, 2017)
    Rrecsys is a novel library in R for developing and assessing recommendation algorithms. In this demo, we extend rrecsys with functions for visual analytics of recommendation performance, that is one of the strong capabilities ...
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    Matrix and tensor decomposition in recommender systems 

    Symeonidis P (Association for Computing Machinery, Inc, 2016)
    This turorial offers a rich blend of theory and practice re- garding dimensionality reduction methods, to address the in- formation overload problem in recommender systems. This problem affects our everyday experience while ...
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    Novelty-Aware Matrix Factorization Based on Items’ Popularity 

    Coba L; Symeonidis P; Zanker M (Springer, 2018)
    The search for unfamiliar experiences and novelty is one of the main drivers behind all human activities, equally important with harm avoidance and reward dependence. A recommender system personalizes suggestions to ...
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    xStreams: Recommending items to users with time-evolving preferences 

    Siddiqui Z; Tiakas E; Symeonidis P; Spiliopoulou M; Manolopoulos Y (Association for Computing Machinery, 2014)
    Over the last decade a vast number of businesses have developed online e-shops in the web. These online stores are supported by sophisticated systems that manage the products and record the activity of customers. There ...
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    Replicating and improving top-n recommendations in open source packages 

    Coba L; Symeonidis P; Zanker M (ACM, 2018)
    Collaborative filtering techniques have been studied extensively during the last decade. Many open source packages (Apache Mahout, LensKit, MyMediaLite, rrecsys etc.) have them implemented, but typically the top-N ...
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    Scalable link prediction in social networks based on local graph characteristics 

    Papadimitriou A; Symeonidis P; Manolopoulos Y (IEEE, 2012)
    Online social networks (OSNs) like Face book, My space, and Hi5 have become popular, because they allow users to easily share content or expand their social circle. OSNs recommend new friends to registered users based on ...
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    Exploring Users' Perception of Rating Summary Statistics 

    Coba L; Symeonidis P; Zanker M (ACM, 2018)
    Collaborative filtering systems heavily depend on user feedback expressed in product ratings to select and rank items to recommend. These summary statistics of rating values carry two important descriptors about the assessed ...
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    Friendlink: Link prediction in social networks via bounded local path traversal 

    Papadimitriou A; Symeonidis P; Manolopoulos Y (IEEE, 2011)
    Online social networks (OSNs) like Facebook, Myspace, and Hi5 have become popular, because they allow users to easily share content or expand their social circle. OSNs recommend new friends to registered users based on ...
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    New perspectives for recommendations in location-based social networks: Time, privacy and explainability 

    Kefalas P; Symeonidis P; Manolopoulos Y (ACM, 2013)
    Online social networks have attracted users' attention in the last decade. Recommendation services constitute a critical functionality of such social platforms: users receive recommendations about resources (documents, ...
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    Social tagging recommender systems 

    Marinho LB; Nanopoulos A; Schmidt-Thieme L; Jäschke R; Hotho A; Stumme G; Symeonidis P (Springer US, 2011)
    The new generation of Web applications known as (STS) is successfully established and poised for continued growth. STS are open and inherently social; features that have been proven to encourage participation. But while ...
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Symeonidis P (21)
Manolopoulos Y (10)Zanker M (5)Coba L (4)Nanopoulos A (4)Papadimitriou A (3)Kefalas P (2)Tiakas E (2)Chairistanidis S (1)Deligiaouri A (1)... View MoreDate Issued2010 - 2019 (18)2007 - 2009 (3)Full Text Availability
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