Abstract is missing.
- Deep Auto-Encoding for Context-Aware Inference of Preferred Items' CategoriesMoshe Unger, Bracha Shapira, Lior Rokach, Ariel Bar. [doi]
- Music Playlist Recommendation via Preference EmbeddingChih-Ming Chen, Chun-Yao Yang, Chih-Chun Hsia, Yian Chen, Ming-Feng Tsai. [doi]
- Tip Ranker: A M.L. Approach to Ranking Short ReviewsEnrique Cruz, Berk Kapicioglu. [doi]
- Memory Priming and User PreferencesEvangelia Anagnostopoulou, Efthimios Bothos, Babis Magoutas, Gregoris Mentzas. [doi]
- Idomaar: A Framework for Multi-dimensional Benchmarking of Recommender AlgorithmsMario Scriminaci, Andreas Lommatzsch, Benjamin Kille, Frank Hopfgartner, Martha Larson, Davide Malagoli, András Serény, Till Plumbaum. [doi]
- Is Readability a Valuable Signal for Hashtag Recommendations?Ion Madrazo Azpiazu, Maria Soledad Pera. [doi]
- How to Survive Dynamic Pricing Competition in E-commerceRainer Schlosser, Martin Boissier 0001, Andre Schober, Matthias Uflacker. [doi]
- Genre Prediction to Inform the Recommendation ProcessNevena Dragovic, Maria Soledad Pera. [doi]
- An Entity Graph Based Recommender SystemSneha Chaudhari, Amos Azaria, Tom M. Mitchell. [doi]
- Item2vec: Neural Item Embedding for Collaborative FilteringOren Barkan, Noam Koenigstein. [doi]
- Detecting Trending Venues Using Foursquare's DataStephanie Yang, Max Sklar. [doi]
- Weighted Random Walks for Meta-Path Expansion in Heterogeneous NetworksFatemeh Vahedian, Robin D. Burke, Bamshad Mobasher. [doi]
- Cross Domain Recommendation Using Vector Space Transfer LearningMasahiro Kazama, István Varga. [doi]
- User Segmentation for Controlling Recommendation DiversityFarzad Eskandanian, Bamshad Mobasher, Robin D. Burke. [doi]
- A Secure Shopping Experience Based on Blockchain and Beacon TechnologyRemo Manuel Frey, Denis Vuckovac, Alexander Ilic. [doi]
- Towards Understanding Latent Factors and User Profiles by Enhancing Matrix Factorization with TagsTim Donkers, Benedikt Loepp, Jürgen Ziegler 0001. [doi]
- Representing Items as Word-Embedding Vectors and Generating Recommendations by Measuring their Linear IndependenceLudovico Boratto, Salvatore Carta, Gianni Fenu, Roberto Saia. [doi]
- Recommendation from Intransitive Pairwise ComparisonsElja Arjas, Arnoldo Frigessi, Valeria Vitelli, Marta Crispino. [doi]
- Combining Dynamic A/B Experimentation and Recommender Systems in MOOCsJoseph Jay Williams, Luong Hoang. [doi]
- rrecsys: An R-package for Prototyping Recommendation AlgorithmsLudovik Çoba, Markus Zanker. [doi]
- Explicit Elimination of Similarity Blocking for Session-based RecommendationMattia Brusamento, Roberto Pagano, Martha Larson, Paolo Cremonesi. [doi]
- MoocRec.com : Massive Open Online Courses Recommender SystemPanagiotis Symeonidis, Dimitrios Malakoudis. [doi]
- Modelling Session Activity with Neural EmbeddingOren Barkan, Yael Brumer, Noam Koenigstein. [doi]
- Dish Discovery via Word Embeddings on Restaurant ReviewsChih-yu Chao, Yi-Fan Chu, Yi Ho, Chuan-Ju Wang, Ming-Feng Tsai. [doi]