Recent Submissions

  • 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 ...
  • 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 ...
  • Transitive node similarity for link prediction in social networks with positive and negative links 

    Symeonidis P; Tiakas E; Manolopoulos Y (ACM, 2010)
    Online social networks (OSNs) like Facebook, and Myspace recommend new friends to registered users based on local features of the graph (i.e. based on the number of common friends that two users share). However, OSNs do ...
  • Text classification by aggregation of SVD eigenvectors 

    Symeonidis P; Kehayov I; Manolopoulos Y (Springer, 2012)
    Text classification is a process where documents are categorized usually by topic, place, readability easiness, etc. For text classification by topic, a well-known method is Singular Value Decomposition. For text classification ...
  • User recommendations based on tensor dimensionality reduction 

    Symeonidis P (Springer, 2009)
    Social Tagging is the process by which many users add metadata in the form of keywords, to annotate and categorize items (songs, pictures, web links, products etc.). Social tagging systems (STSs) can recommend users with ...
  • Recommending friends and locations over a heterogeneous spatio-temporal graph 

    Kefalas P; Symeonidis P (Springer Verlag, 2015)
    Recommender systems in location-based social networks (LBSNs), such as Facebook Places and Foursquare, have focused on recommending friends or locations to registered users by combining information derived from explicit ...
  • Multiway spectral clustering link prediction in protein-protein interaction networks 

    Iakovidou N; Symeonidis P; Manolopoulos Y (IEEE, 2010)
    An increasing number of observations support the hypothesis that the vast majority of biological functions involve interactions between proteins and that the complexity of living systems arises as a result of such interactions. ...
  • Content-based dimensionality reduction for recommender systems 

    Symeonidis P (Springer, 2008)
    Recommender Systems are gaining widespread acceptance in e-commerce applications to confront the information overload problem. Collaborative Filtering (CF) is a successful recommendation technique, which is based on past ...
  • CheckInShop. eu: A Sensor-based Recommender System for micro-location Marketing 

    Symeonidis P; Chairistanidis S (ACM Digital Library, 2017)
    CheckInShop is an app that employs sensors to capture the user preferences in physical stores and provide either micro-location marketing or product recommendations. By utilizing iBeacon technology and with the exploitation ...
  • 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 ...
  • Collaborative filtering process in a whole new light 

    Symeonidis P; Nanopoulos A; Papadopoulos A; Manolopoulos Y (IEEE, 2006)
    Collaborative Filtering (CF) Systems are gaining widespread acceptance in recommender systems and e-commerce applications. These systems combine information retrieval and data mining techniques to provide recommendations ...
  • Nearest-biclusters collaborative filtering with constant values 

    Symeonidis P; Nanopoulos A; Papadopoulos A; Manolopoulos Y (Springer, 2007)
    Collaborative Filtering (CF) Systems have been studied extensively for more than a decade to confront the "information overload" problem. Nearest-neighbor CF is based either on common user or item similarities, to form the ...
  • 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, ...
  • Product recommendation and rating prediction based on multi-modal social networks 

    Symeonidis P; Tiakas E; Manolopoulos Y (ACM, 2011)
    Online Social Rating Networks (SRNs) such as Epinions and Flixter, allow users to form several implicit social networks, through their daily interactions like co-commenting on the same products, or similarly co-rating ...
  • Collaborative filtering based on user trends 

    Symeonidis P; Nanopoulos A; Papadopoulos A; Manolopoulos Y (Springer, 2007)
    Recommender systems base their operation on past user ratings over a collection of items, for instance, books, CDs, etc. Collaborative Filtering (CF) is a succesful recommendation technique. User ratings are not expected ...
  • 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 ...
  • A data generator for multi-stream data 

    Siddiqui ZF; Spiliopoulou M; Symeonidis P; Tiakas E (NA, 2011)
    We present a stream data generator. The generator is mainly intended for multiple interrelated streams, in particular for objects with temporal properties, which are fed by dependent streams. Such data are e.g. customers ...
  • Decision Making Strategies Differ in the Presence of Collaborative Explanations: Two Conjoint Studies 

    Coba L; Zanker M; Rook L; Symeonidis P (ACM Digital Library, 2019)
    Rating-based summary statistics are ubiquitous in e-commerce, and often are crucial components in personalized recommendation mechanisms. Especially visual rating summarizations have been identified as important means to ...
  • Geo-social recommendations based on incremental tensor reduction and local path traversal 

    Symeonidis P; Papadimitriou A; Manolopoulos Y; Senkul P; Toroslu I (ACM, 2011)
    Social networks have evolved with the combination of geographical data, into Geo-social networks (GSNs). GSNs give users the opportunity, not only to communicate with each other, but also to share images, videos, locations, ...
  • MoocRec.com: Massive open online courses recommender system 

    Symeonidis P; Malakoudis D (CEUR-WS.org, 2016)
    Massive open online courses (MOOCs) have recently gained a huge users' attention on the Web. They are considered as a highly promising form of teaching from leading universities such as Stanford and Berkeley. MoocRec.com ...

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