Poster-RecSys 2016
Poster Proceedings of ACM RecSys 2016

Table of Contents

• Preface
  
  

• MoocRec.com : Massive Open Online Courses Recommender System
  Panagiotis Symeonidis, Dimitrios Malakoudis
  
• Recommendation from Intransitive Pairwise Comparisons
  Elja Arjas, Arnoldo Frigessi, Valeria Vitelli, Marta Crispino
  
• A Secure Shopping Experience Based on Blockchain and Beacon Technology
  Remo Manuel Frey, Denis Vučkovac, Alexander Ilic
  
• Cross Domain Recommendation Using Vector Space Transfer Learning
  Masahiro Kazama, Istvan Varga
  
• Genre Prediction to Inform the Recommendation Process
  Nevena Dragovic, Maria Soledad Pera
  
• An Entity Graph Based Recommender System
  Sneha Chaudhari, Amos Azaria, Tom Mitchell
  
• Explicit Elimination of Similarity Blocking for Session-based Recommendation
  Mattia Brusamento, Roberto Pagano, Martha Larson, Paolo Cremonesi
  
• Modelling Session Activity with Neural Embedding
  Oren Barkan, Yael Brumer, Noam Koenigstein
  
• Detecting Trending Venues Using Foursquare’s Data
  Stephanie Yang, Max Sklar
  
• How to Survive Dynamic Pricing Competition in E-commerce
  Rainer Schlosser, Martin Boissier, Andre Schober, Matthias Uflacker
  
• Weighted Random Walks for Meta-Path Expansion in Heterogeneous Networks
  Fatemeh Vahedian, Robin Burke, Bamshad Mobasher
  
• rrecsys: An R-package for Prototyping Recommendation Algorithms
  Ludovik Çoba, Markus Zanker
  
• Item2vec: Neural Item Embedding for Collaborative Filtering
  Oren Barkan, Noam Koenigstein
  
• Idomaar: A Framework for Multi-dimensional Benchmarking of Recommender Algorithms
  Mario Scriminaci, Andreas Lommatzsch, Benjamin Kille, Frank Hopfgartner, Martha Larson, Davide Malagoli, Andras Sereny, Till Plumbaum
  
• Tip Ranker: A M.L. Approach to Ranking Short Reviews
  Enrique Cruz, Berk Kapicioglu
  
• Deep Auto-Encoding for Context-Aware Inference of Preferred Items’ Categories
  Moshe Unger, Bracha Shapira, Lior Rokach, Ariel Bar
  
• Music Playlist Recommendation via Preference Embedding
  Chih-Ming Chen, Chun-Yao Yang, Chih-Chun Hsia, Yian Chen, Ming-Feng Tsai
  
• Dish Discovery via Word Embeddings on Restaurant Reviews
  Chih-Yu Chao, Yi-Fan Chu, Yi Ho, Chuan-Ju Wang, Ming-Feng Tsai
  
• Combining Dynamic A/B Experimentation and Recommender Systems in MOOCs
  Joseph Jay Williams, Luong Hoang
  
• Towards Understanding Latent Factors and User Profiles by Enhancing Matrix Factorization with Tags
  Tim Donkers, Benedikt Loepp, Jürgen Ziegler
  
• Is Readability a Valuable Signal for Hashtag Recommendations?
  Ion Madrazo, Maria Soledad Pera
  
• Memory Priming and User Preferences
  Evagelia Anagnostopoulou, Efthimios Bothos, Babis Magoutas, Gregoris Mentzas
  
• Representing Items as Word-Embedding Vectors and Generating Recommendations by Measuring their Linear Independence
  Ludovico Boratto, Salvatore Carta, Gianni Fenu, Roberto Saia
  
• User Segmentation for Controlling Recommendation Diversity
  Farzad Eskandanian, Bamshad Mobasher, Robin Burke