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ORCIDRecSys 2017: Como, Italy - Posters
- Domonkos Tikk, Pearl Pu:
Proceedings of the Poster Track of the 11th ACM Conference on Recommender Systems (RecSys 2017), Como, Italy, August 28, 2017. CEUR Workshop Proceedings 1905, CEUR-WS.org 2017 - Mesut Kaya, Derek G. Bridge:
Intent-Aware Diversification using Item-Based SubProfiles. - Rose Catherine, Kathryn Mazaitis, Maxine Eskénazi, William W. Cohen:
Explainable Entity-based Recommendations with Knowledge Graphs. - Kuan Liu, Prem Natarajan:
WMRB: Learning to Rank in a Scalable Batch Training Approach. - Arpit Rana, Derek Bridge:
Explanation Chains: Recommendations by Explanation. - Masahiro Kazama, István Varga:
Multi Cross Domain Recommendation Using Item Embedding and Canonical Correlation Analysis. - Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer, Paolo Cremonesi:
The Importance of Song Context in Music Playlists. - Erzsébet Frigó, Róbert Pálovics, Domokos Kelen, Levente Kocsis, András A. Benczúr:
Alpenglow: Open Source Recommender Framework with Time-aware Learning and Evaluation. - Felipe del-Rio, Denis Parra, Jovan Kuzmicic, Erick Svec:
Towards a Recommender System for Undergraduate Research. - Fedelucio Narducci, Marco de Gemmis, Pasquale Lops, Giovanni Semeraro:
Recommender Systems in the Internet of Talking Things (IoTT). - Iacopo Vagliano, Diego Monti, Maurizio Morisio:
SemRevRec: A Recommender System based on User Reviews and Linked Data. - Jacek Wasilewski, Neil Hurley:
How Diverse Is Your Audience? Exploring Consumer Diversity in Recommender Systems. - Young Park:
A Recommender System for Personalized Exploration of Majors, Minors, and Concentrations. - Andrea Gigli, Fabrizio Lillo, Daniele Regoli:
Recommender Systems for Banking and Financial Services. - Oghenemaro Anuyah, Ion Madrazo Azpiazu, David McNeill, Maria Soledad Pera:
Can Readability Enhance Recommendations on Community Question Answering Sites? - F. Maxwell Harper:
Recommender Popularity Controls: An Observational Study. - Anusuriya Devaraju, Shlomo Berkovsky:
Do Users Matter? The Contribution of User-Driven Feature Weights to Open Dataset Recommendations. - Himan Abdollahpouri, Steve Essinger:
Towards Effective Exploration/Exploitation in Sequential Music Recommendation. - Byungsoo Jeon, Chanju Kim, Adrian Kim, Dongwon Kim, Jangyeon Park, JungWoo Ha:
Music Emotion Recognition via End-to-End Multimodal Neural Networks. - Donghyun Kim, Hayong Shin:
An Explanatory Matrix Factorization with User Comments Data. - Michael D. Ekstrand, Maria Soledad Pera:
The Demographics of Cool: Popularity and Recommender Performance for Different Groups of Users. - Leonardo Cella, Romaric Gaudel, Paolo Cremonesi:
Kernalized Collaborative Contextual Bandits. - Catalin-Mihai Barbu, Jürgen Ziegler:
Users' Choices About Hotel Booking: Cues for Personalizing the Presentation of Recommendations. - Gabriel Sepulveda, Vicente Dominguez, Denis Parra:
pyRecLab: A Software Library for Quick Prototyping of Recommender Systems.
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