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WSDM
2016
ACM
65views Data Mining» more  WSDM 2016»
10 years 11 days ago
Modeling Intransitivity in Matchup and Comparison Data
We present a method for learning potentially intransitive preference relations from pairwise comparison and matchup data. Unlike standard preference-learning models that represent...
Shuo Chen, Thorsten Joachims
WSDM
2016
ACM
115views Data Mining» more  WSDM 2016»
10 years 11 days ago
Modeling and Predicting Learning Behavior in MOOCs
Massive Open Online Courses (MOOCs), which collect complete records of all student interactions in an online learning environment, offer us an unprecedented opportunity to analyze...
Jiezhong Qiu, Jie Tang, Tracy Xiao Liu, Jie Gong, ...
WSDM
2016
ACM
66views Data Mining» more  WSDM 2016»
10 years 11 days ago
Ensemble Models for Data-driven Prediction of Malware Infections
Given a history of detected malware attacks, can we predict the number of malware infections in a country? Can we do this for different malware and countries? This is an importan...
Chanhyun Kang, Noseong Park, B. Aditya Prakash, Ed...
WSDM
2016
ACM
48views Data Mining» more  WSDM 2016»
10 years 11 days ago
To Suggest, or Not to Suggest for Queries with Diverse Intents: Optimizing Search Result Presentation
We propose a method of optimizing search result presentation for queries with diverse intents, by selectively presenting query suggestions for leading users to more relevant searc...
Makoto P. Kato, Katsumi Tanaka
WSDM
2016
ACM
56views Data Mining» more  WSDM 2016»
10 years 11 days ago
Geographic Segmentation via Latent Poisson Factor Model
Discovering latent structures in spatial data is of critical importance to understanding the user behavior of locationbased services. In this paper, we study the problem of geogra...
Rose Yu, Andrew Gelfand, Suju Rajan, Cyrus Shahabi...