[Our apologies for cross posting]

 

ACM International Conference on Recommender Systems (RecSys) 2013 Oct 12-16,
2013, Hong Kong, China

 

======================================================================

Registration

======================================================================

 

Please register as soon as possible
(https://www.regonline.com/Register/Checkin.aspx?EventID=1263861) to ensure
that you join this rich experience in Recommendation System area's biggest
event!

 

EARLY: ON OR BEFORE SEPT 7

LATE : ON OR AFTER SEPT 8

ON-SITE: ON OR AFTER OCT 5

http://recsys.acm.org/recsys13/registration/

 

======================================================================

Program

======================================================================

 

All events have lunch breaks at 12.30h-14.00h and coffee breaks at
10.15h-10-45h and 15.45h-16.15h, respectively.

http://recsys.acm.org/recsys13/program/

 

===========

Sat, Oct 12

===========

-        Doctoral Symposium

(Room LT-11, 8.30h – 18.00h)

-        Workshop Decisions: Human Decision Making in Recommender Systems 

(Room LT-15, 8.30h – 18.00h) 

-        Workshop RepSys: Reproducibility and Replication in Recommender
Systems Evaluation 

(Room LT-16, 8.30h – 18.00h) 

-        Workshop CrowdRec: Crowdsourcing and Human Computation for
Recommender Systems 

(Room LT-10, 14.00h – 18.00h) 

-        Tutorial Mining Social Networks for Recommendation 

(Room LT-13, 8.30h – 10.15h) 

-        Tutorial Learning to Rank 

(Room LT-13, 14.00h – 15.45h)

 

===========

Sun, Oct 13

===========

-        Workshop RSWeb: Recommender Systems and the Social Web

(Room LT-7, 8.30h – 18.00h) 

-        Workshop NRS: News Recommender Systems Workshop and Challenge

(Room LT-15, 8.30h – 12.30h) 

-        Workshop SeRSy: Recommender Systems meet Big Data and Semantic
Technologies 

(Room LT-16, 14.00h – 18.00h) 

-        Workshop LargeScale: Large Scale Recommendation Systems: Research
and Best Practice 

(Room LT-14, 8.30h – 18.00h) 

-        Workshop Workshop on the RecSys Challenge 2013 

(Room LT-17, 8.30h – 18.00h) 

-        Tutorial Beyond Friendship:­ The Art, Science and Applications of
Recommending People to People in Social Networks 

(Room LT-13, 8.30h – 10.15h) 

-        Tutorial Preference Handling 

(Room LT-13, 14.00h – 15.45h)

 

===========

Mon, Oct 14

===========

08:30 – 10:15 — OPENING, KEYNOTE: INFORMATION EXTRACTION, SENTIMENT
ANALYSIS, AND RECOMMENDATIONS

-        Professor Oren Etzioni (University of Washington, Seattle, WA, USA)

 

10:15 – 10:45 — COFFEE BREAK

 

10:45 – 12:30 — SESSION 1: CONTEXT-AWARE

 

-        Context-Aware Review Helpfulness Rating Prediction 

by Jiliang Tang 

 

-        Query-Driven Context Aware Recommendation 

by Negar Hariri; Bamshad Mobasher; Robin Burke 

 

-        Location-aware Music Recommendation Using Auto-Tagging and Hybrid
Matching 

by Marius Kaminskas; Francesco Ricci; Markus Schedl 

 

-        Spatial Topic Modeling in Online Social Media for Location
Recommendation 

by Bo Hu; Martin Ester 

 

12:30 – 14:00 — LUNCH

 

14:00 – 15:45 — SESSION 2: METHODS, ALGORITHMS, AND THEORIES

 

-        Orthogonal Query Recommendation

by Hossein Vahabi; Margareta Ackerman; David Loker; Ricardo Baeza-Yates;
Alejandro Lopez-Ortiz 

 

-        Understanding and Improving Relational Matrix Factorization in
Recommender Systems 

by Li Pu; Boi Faltings 

 

-        Retargeted Matrix Factorization for Collaborative Filtering 

by Oluwasanmi Koyejo; Sreangsu Acharyya; Joydeep Ghosh 

 

-        Trading-off Among Accuracy; Similarity; Diversity; and Long-tail: A
Graph-based Recommendation Approach 

by Lei Shi 

 

-        Nonlinear Latent Factorization by Embedding Multiple User Interests


by Jason Weston; Ron Weiss; Hector Yee

 

15:45 – 16:15 — COFFEE BREAK

 

16:15 – 18:00 — SESSION 3: SOCIAL MEDIA AND RECOMMENDER SYSTEMS

 

-        Diffusion-aware Personalized Social Update Recommendation 

by Ye Pan; Kailong Chen; Yong Yu 

 

-        Recommending Branded Products from Social Media 

by Yongzheng Zhang; Marco Pennacchiotti 

 

-        Top-N Recommendations from Implicit Feedback leveraging Linked Open
Data 

by Vito Claudio Ostuni; Tommaso Di Noia; Eugenio Di Sciascio; Roberto
Mirizzi 

 

-        Exploring Temporal Effects for Location Recommendation on
Location-Based Social Networks 

by Huiji Gao; Jiliang Tang; Xia Hu; Huan Liu 

 

-        The Curated Web: A Recommendation Challenge 

by Zurina Saaya; Rachael Rafter; Markus Schaal; Barry Smyth 

 

18:00 – 21:00 — POSTER AND DEMO RECEPTION

 

-        Creative Media Centre, City University of Hong Kong

 

===========

Tue, Oct 15

===========

08:30 – 10:15 SESSION 4: MEDIA RECOMMENDATION

 

-        Personalized News Recommendation with Context Trees 

by Florent Garcin; Christos Dimitrakakis; Boi Faltings 

 

-        What to Read Next?: Making Personalized Book Recommendations for
K-12 Users 

by Maria Pera; Yiu-Kai Ng 

 

-        Movie Recommender System for Profit Maximization 

by Amos Azaria; Avinatan Hassidim; Sarit Kraus; Adi Eshkol; Ofer Weintraub;
Irit Netanely 

 

-        Xbox Movies Recommendations: Variational Bayes Matrix Factorization
with Embedded Feature Selection 

by Noam Koenigstein; Ulrich Paquet 

 

-        Personalized Next-song Recommendation in Online Karaokes 

by Xiang Wu; Qi Liu; Enhong Chen; Jingsong Lv; Can Cao; Guoping Hu

 

10:15 – 10:45 COFFEE BREAK

 

10:45 – 12:30 KEYNOTE: RECOMMENDATION IN ONLINE ADVERTISING

 

-        Dr. Dou Shen (Director of Advertising, Baidu, China) 

 

12:30 – 14:00 LUNCH

 

14:00 – 15:45 SESSION 5: USER EXPERIENCE

 

-        Topic Diversity in Tag Recommendation

by Fabiano Belém Rodrygo Santos; Marcos Goncalves; Jussara Almeida 

 

-        Rating support interfaces to improve user experience and
recommender accuracy 

by Tien T. Nguyen; Daniel Kluver; Ting-Yu Wang; Pik-Mai Hui; Michael
Ekstrand; Martijn C. Willemsen; John Riedl

 

-        ReComment: Towards Critiquing-based Recommendation with Speech
Interaction 

by Peter Grasch; Alexander Felfernig; Florian Reinfrank 

 

-        Hidden Factors and Hidden Topics: Understanding Rating Dimensions
with Review Text 

by Julian McAuley; Jure Leskovec 

 

-        Improving Augmented Reality Using Recommender Systems 

by Zhuo Zhang; Shang Shang; Sanjeev Kulkarni; Pan Hui

 

15:45 – 16:15 COFFEE BREAK

 

16:15 – 18:00 SESSION 6: BEYOND RATINGS

 

-        Exploiting non-content taste attributes through hybrid
recommendation method 

by Fernando Mourão Leonardo Rocha; Joseph Konstan; Wagner Meira Jr.

 

-        Hybrid Event Recommendation using Linked Data and User Diversity 

by Houda Khrouf; Raphael Troncy 

 

-        Pairwise Feedback in Recommendation: Experiments with Community
Recommendation on LinkedIn 

by Amit Sharma; Baoshi Yan 

 

-        Which app will you use next? Collaborative Filtering with
Interactional Context 

by Nagarajan Natarajan; Donghyuk Shin; Inderjit Dhillon 

 

-        A Food Recommender for Patients in a Care Facility 

by Toon De Pessemier; Simon Dooms; Luc Martens 

 

18:00 – 21:00 BANQUET

 

===========

Wed, Oct 16

===========

08:30-10:15 INDUSTRY SESSION

 

10:15 – 10:45 COFFEE BREAK

 

10:45 – 12:30 KEYNOTE: RECOMMENDATION FOR HAPPINESS

 

-        Yan, Mu (Co-founder & Chief Happiness Officer, Baihe.com, China) 

 

12:30 – 14:00 LUNCH

 

14:00 – 15:45 SESSION 7: METHODS, ALGORITHMS, AND THEORIES

 

-        Rating-Prediction and Ranking

by Harald Steck

 

-        You Are What You Consume: A Bayesian Method For Personalized
Recommendations 

by Konstantinos Babas; Georgios Chalkiadakis; Evangelos Tripolitakis 

 

-        To Personalize or Not: A Risk Management Perspective 

by Weinan Zhang; Jun Wang; Bowei Chen; Xiaoxue Zhao 

 

-        Online Multi-Task Collaborative Filtering for On-the-Fly
Recommender Systems 

by Jialei Wang; Steven C.H. Hoi; Peilin Zhao 

 

-        Learning to Rank Recommendations with the k-Order Statistic Loss 

by Jason Weston; Hector Yee; Ron Weiss

 

15:45 – 16:15 COFFEE BREAK

 

16:15 – 18:00 SESSION 8: SCALABILITY

 

-        A Fast Parallel SGD for Matrix Factorization in Shared Memory
Systems 

by Yong Zhuang; Wei-Sheng Chin; Yu-Chin Juan; Chih-Jen Lin

 

-        DrunkardMob: Billions of Random Walks on Just a PC 

by Aapo Kyrola 

 

-        Using Set Cover to Optimize Recommendation Systems in E-Commerce 

by Mikael Hammar; Robin Karlsson; Bengt Nilsson 

 

-        Efficient Top-N Recommendation for Very Large Scale Binary Rated
Datasets 

by Fabio Aiolli 

 

-        Distributed Matrix Factorization with MapReduce using a series of
Broadcast-Joins 

by Sebastian Schelter; Christoph Boden; Martin Schenck; Alexander
Alexandrov; Volker Markl

 

 


############################

To unsubscribe from the MM-INTEREST list:
write to: mailto:[log in to unmask]
or click the following link:
http://listserv.acm.org/scripts/wa-ACMLPX.exe?SUBED1=MM-INTEREST&A=1