RecSys Readings (Spring 2019)

This is the reading list for my Spring 2019 offering of Recommender Systems (CS 538).

Week 1
William Hill, Larry Stead, Mark Rosenstein, and George Furnas. 1995. Recommending and Evaluating Choices in a Virtual Community of Use. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’95), 194–201. doi:10.1145/223904.223929
Week 2
J. Ben Schafer, Joseph Konstan, and John Riedl. 1999. Recommender Systems in e-Commerce. In Proceedings of the 1st ACM Conference on Electronic Commerce (EC ’99), 158–166. doi:10.1145/336992.337035
Week 3

María Hernández-Rubio, Iván Cantador, and Alejandro Bellogín. 2018. A comparative analysis of recommender systems based on item aspect opinions extracted from user reviews. User Model. User-adapt Interact. (November 2018). DOI:10.1007/s11257-018-9214-9

Focusing on sections 1, 2, 4, and 7 (this paper is long).

Week 4
Xia Ning and George Karypis. 2011. SLIM: Sparse Linear Methods for Top-N Recommender Systems. In Proceedings of the 2011 IEEE 11th International Conference on Data Mining (ICDM ’11), 497–506. DOI:10.1109/ICDM.2011.134
Week 5
Deborah Cohen, Michal Aharon, Yair Koren, Oren Somekh, and Raz Nissim. 2017. Expediting Exploration by Attribute-to-Feature Mapping for Cold-Start Recommendations. In Proceedings of the Eleventh ACM Conference on Recommender Systems (RecSys ’17). ACM, New York, NY, USA, 184-192. DOI:10.1145/3109859.3109880
Week 7
Martijn C. Willemsen, Bart P. Knijnenburg, Mark P. Graus, Linda C. M. Velter-Bremmers, and Kai Fu. 2011. Using latent features diversification to reduce choice difficulty in recommendation lists. In Proceedings of the RecSys 2011 Workshop on Human Decision Making in Recommender Systems (Decisions@RecSys’11).
Week 8
Alan Said and Alejandro Bellogin. 2014. Comparative Recommender System Evaluation: Benchmarking Recommendation Frameworks. In Proceedings of the Eighth ACM Conference on Recommender Systems (RecSys ’14) (RecSys ’14), 129–136. DOI:10.1145/2645710.2645746