Publications
Attentive Item2Vec: Neural Attentive User Representations (pdf)
Oren Barkan, Caciularu, Ori Katz, Noam Koenigstein 
 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP'20)
Neural Attentive Multiview Machines (pdf)
Oren Barkan, Ori Katz, Noam Koenigstein 
 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP'20)
When Actions Speak Louder than Clicks: A Combined Model of Purchase Probability and Long-term Customer Satisfaction (pdf)
Gal Lavee, Noam Koenigstein, Oren Barkan 
ACM Conference on 
	Recommender Systems (RecSys'19), September 2019
CB2CF: A Neural Multiview Content-to-Collaborative Filtering Model for Completely Cold Item Recommendations (pdf)
Oren Barkan, Noam Koenigstein, Eylon Yogev, Ori Katz
ACM Conference on 
	Recommender Systems (RecSys'19), September 2019
Pick & Merge: An Efficient Item Filtering Scheme for Windows Store Recommendations  (pdf)
Adi Makmal, Jonathan Ephrath, Hilik Berezin, Liron Allerhand, Nir Nice, Noam Koenigstein
ACM Conference on 
	Recommender Systems (RecSys'19), September 2019
Rethinking Collaborative Filtering: A 
	Practical Perspective on State-Of-The-Art Research Based on Real-World 
	Insights and Challenges (Invited Talk)
Noam Koenigstein
ACM Conference on 
	Recommender Systems (RecSys'17), August 2017
Groove Radio: A Bayesian Hierarchical Model 
	for Personalized Playlist Generation (pdf)
	Shay Ben Elazar, Gal Lavee, Noam Koenigstein, Oren Barkan, Hilik 
	Berezin, Ulrich Paquet and Tal Zaccai
ACM Conference on Web Search 
	and Data Mining (WSDM'17), Cambridge UK, February 2017.
Low-Rank Factorization of Determinantal 
	Point Processes for Recommendation (pdf)
	Mike Gartrell, Ulrich Paquet, Noam Koenigstein
	The Fourteenth AAAI Conference on Artificial Intelligence, 2017.
Bayesian Low-Rank Determinantal Point 
	Processes
	Mike Gartrell, Ulrich Paquet, Noam Koenigstein
ACM Conference on 
	Recommender Systems (RecSys'16), September 2016, Boston, MA, USA..
Item2Vec: Neural Item Embedding for 
	Collaborative Filtering (pdf)
	Oren Barkan, Noam Koenigstein
	arXiv:1603.04259, 2016.
Wikipedia links
	
	here and
	
	here.
 Beyond Collaborative Filtering: The 
	List Recommendation Problem (pdf)
	Oren Sar Shalom, Noam Koenigstein, Ulrich Paquet, Hastagiri P. 
	Vanchinathan
International World Wide Web Conference (WWW'16), 
	April 2016, Montreal, Canada.
 Speeding Up the Xbox Recommender System Using 
	a Euclidian Transformation for Inner Product Spaces (pdf)
	Yoram Bachrach, Yehuda Finkelstein, Ran Gilad-Bachrach, Liran 
	Katzir, Noam Koenigstein, Nir Nice, Ulrich Paquet
ACM Conference on 
	Recommender Systems (RecSys'14), October 2014, San Fransisco, CA, USA.
A Hybrid Explanations Framework for 
	Collaborative Filtering Recommender Systems (poster) (pdf)
	Shay Ben Elazar, Noam Koenigstein
ACM Conference on 
	Recommender Systems (RecSys'14), October 2014, San Fransisco, CA, USA.
A Scalable Bayesian Alternative to Density 
	Estimation with a Bilinear Softmax Function (pdf)
	Ulrich Paquet, Noam Koenigstein, Ole Winther
Annual 
	Conference on Neural Information Processing Systems (NIPS'14) Workshop on 
	Personalization Methods and Applications, December 2014, Montreal, 
	Canada.
A Large-scale Exploration of Group Viewing 
	Patterns (pdf)
	Best paper runner up
Allison J.B. 
	Chaney, Mike Gartrell, Jake M. Hofman, John Guiver, Noam Koenigstein, 
	Pushmeet Kohli, Ulrich Paquet
TVX - ACM International Conference on 
	Interactive Experiences for Television and Online Video, June 2014, 
	Newcastle , UK.
Xbox Movies Recommendations: Variational 
	Bayes Matrix Factorization with Embedded Feature Selection (pdf)
	Noam Koenigstein, Ulrich Paquet
ACM Conference on 
	Recommender Systems (RecSys'13), October 2013, Hong Kong, China.
Towards Scalable and Accurate Item-Oriented 
	Recommendations (short paper) (pdf)
	Noam Koenigstein, Yehuda Koren
ACM Conference on Recommender 
	Systems (RecSys'13), October 2013, Hong Kong, China.
Sage: Recommender Engine as a Cloud Service 
	(demo paper) (pdf)
Royi Ronen, 
	Noam Koenigstein, Elad Ziklik, Mikael Sitruk, Ronen Yaari, Neta Haiby-Weiss
	ACM Conference on Recommender Systems (RecSys'13), October 2013, 
	Hong Kong, China.
Selecting Content-Based Features for 
	Collaborative Filtering Recommenders (short paper) (pdf)
	Royi Ronen, Noam Koenigstein, Elad Ziklik, Nir Nice
ACM 
	Conference on Recommender Systems (RecSys'13), October 2013, Hong Kong, 
	China.
One-class Collaborative Filtering with Random Graphs (pdf)
	Noam Koenigstein, Ulrich Paquet
International World Wide Web 
	Conference (WWW'13), May 2013, Rio de Janeiro, Brazil.
The Xbox Recommendation System (short paper) 
	(pdf)
Noam Koenigstein, Nir 
	Nice, Ulrich Paquet, Nir Schleyen
ACM Conference on Recommender 
	Systems (RecSys'12), September 2012, Dublin, Ireland.
Efficient Retrieval of Recommendations in a Matrix Factorization 
	Framework (pdf)
Noam 
	Koenigstein, Parikshit Ram, Yuval Shavitt
ACM International 
	Conference on Information and Knowledge Management (CIKM'12), November 
	2012, Maui, HI, USA.
Yahoo! Music Recommendations: Modeling Music Ratings with 
	Temporal Dynamics and Taxonomy (pdf)
	Gideon Dror, Noam Koenigstein and Yehuda Koren
ACM Conference on 
	Recommender Systems (RecSys'11)}, October 2011, Chicago, IL, USA.
The Yahoo! Music Dataset and KDDCup’11 (pdf)
	Gideon Dror, Noam Koenigstein, Yehuda Koren, Markus Weimer
	The 7th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD): 
	KDD Cup 2011 Workshop, August 2011, San Diego, CA, USA.
Analyzing The DC File Sharing Network (short 
	paper) (pdf)
Pavel Gurvich, Noam 
	Koenigstein, Yuval Shavitt
The IEEE International Conference on 
	Peer-to-Peer Computing (P2P'10), August 2010, Delft, The Netherland.
Collaborative Filtering Based on P2P Networks (pdf)
	Noam Koenigstein, Gert Lanckriet, Brian McFee, Yuval Shavitt
	International Society for Music Information Retrieval (ISMIR'10), 
	August 2010, Utrecht, The Netherland
On the Applicability of Peer-to-Peer Data in Music Information 
	Retrieval Research (pdf)
Noam 
	Koenigstein, Yuval Shavitt, Ela Weinsberg, Udi Weinsberg
	International Society for Music Information Retrieval (ISMIR'10), 
	August 2010, Utrecht, The Netherland.
What’s Hot? Estimating Country Specific 
	Artist Popularity (pdf)
Markus 
	Schedl, Tim Pohle, Noam Koenigstein, Peter Knees
International 
	Society for Music Information Retrieval (ISMIR'10), August 2010, 
	Utrecht, The Netherland.
A Framework for Extracting Musical 
	Similarities From Peer-To-Peer Networks (pdf)
	Noam Koenigstein, Yuval Shavitt, Ela Weinsberg, Udi Weinsberg
AdMIRe: 
	International Workshop on Advances in Music Information Research 2010 (In 
	Conjunction with the ICME 2010), July 2010, Singapore.
Song Ranking Based on Piracy in Peer-to-Peer Networks (pdf)
	Noam Koenigstein, Yuval Shavitt
International Society for Music 
	Information Retrieval (ISMIR'09), October 2009, Kobe, Japan.
Predicting Billboard Success Using Data-Mining in P2P Networks (pdf)
	Noam Koenigstein, Yuval Shavitt, Noa Zilberman
AdMIRe: 
	International Workshop on Advances in Music Information Research 2009 (In 
	Conjunction with the IEEE International Symposium on Multimedia 2009), 
	December 2009, San Diego, CA, USA.
Spotting Out Emerging Artists Using Geo-Aware Analysis of P2P 
	Query Strings (short presentation, full paper) (pdf)
	Noam Koenigstein, Yuval Shavitt, Tomer Tankel
The ACM SIGKDD 
	Conference on Knowledge Discovery and Data Mining (KDD'09), Las Vegas, 
	NV, USA, August 2008.
Journals
The Yahoo! Music Dataset and KDDCup’11 (pdf)
	Gideon Dror, Noam Koenigstein, Yehuda Koren, Markus Weimer
	Journal of Machine Learning Research (JMLR), 17:1-12. 2011.
Web Scale Media Recommendation Systems (pdf)
	Gideon Dror, Noam Koenigstein, Yehuda Koren
Proceedings of 
	the IEEE, 100 (9), 2722-2736, 2012.
Talent Scouting in P2P Networks (pdf)
	Noam Koenigstein, Yuval Shavitt
Computer Networks, 
	56(3):970-982, February 2012
Measuring the Validity of Peer-to-Peer Data 
	for Information Retrieval Applications (pdf)
	Noam Koenigstein, Yuval Shavitt, Ela Weinsberg, Udi Weinsberg
	Computer Networks, 56(3):1092-1102, February 2012.
Other
My Ph.D. dissertation can be found here.