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UBC Presence at SIGKDD 2014

Data mining researchers from the UBC Department of Computer Science presented three papers and organized a workshop at KDD 2014, held in New York City, August 24-27. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) is a premier interdisciplinary conference that brings together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data. With an amazing 2,300 people attending (twice the size of KDD-2013), KDD 2014 showed that it was not just the leading research conference in Data Mining, Data Science, and Knowledge Discovery, but also the largest conferences in the field.

More information about KDD 2014 can be found at https://www.kdd.org/kdd2014/ and at https://www.kdnuggets.com/2014/08/kdd-2014-biggest-best-booming-data-science-meeting.html.

Here is the information on the papers presented by DMM:

Optimal Recommendations Under Attraction, Aversion, and Social Influence

Wei Lu (University of British Columbia), Stratis Ioannidis (Technicolor Research), Smriti Bhagat (Technicolor Research), Laks V.S. Lakshmanan (University of British Columbia)

On Social Event Organization

Keqian Li (University of British Columbia), Wei Lu (University of British Columbia), Smriti Bhagat (Technicolor Research), Laks V.S. Lakshmanan (University of British Columbia), Cong Yu (Google Research)

Modeling Impression Discounting in Large-scale Recommender Systems

Pei Lee (University of British Columbia), Laks V.S. Lakshmanan (University of British Columbia), Mitul Tiwari (LinkedIn Corporation), Sam Shah (LinkedIn Corporation)

Raymond Ng organized a workshop: Outlier Detection and Description under Data Diversity