Complete list of publications

  1. A comprehensive survey of neighborhood-based recommendation methods.

    Xia Ning, Christian Desrosiers, and George Karypis. In Recommender Systems Handbook; 2nd edition, 2015.

  1. Understanding Computer Usage Evolution.

    David C. Anastasiu, Al M. Rashid, Andrea Tagarelli, and George Karypis. 31st IEEE International Conference on Data Engineering (ICDE), 2015.

  1. Evaluation of Connected-Component Labeling Algorithms for Distributed-Memory Systems.

    Jeremy Iverson, Chandrika Kamath, and George Karypis. Parallel Computing, Volume 44, Pages 53–68, 2015.

  1. NLMF: NonLinear Matrix Factorization Methods for Top-N Recommender Systems.

    Santosh Kabbur and George Karypis. 7th ICDM International Workshop on Domain Driven Data Mining (DDDM), 2014.

  1. Memory-Efficient Parallel Computation of Tensor and Matrix Products for Big Tensor Decomposition.

    Niranjay Ravindran, Nicholas D. Sidiropoulos, Shaden Smith, and George Karypis. 28th Asilomar Conference on Signals, 2014.

  1. HOSLIM: Higher-Order Sparse Linear Method for Top-N Recommender Systems.

    Evangelia Christakopoulou and George Karypis. 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2014.

  1. Algorithms for Mining the Coevolving Relational Motifs in Dynamic Networks.

    Rezwan Ahmed and George Karypis. UMN CS 14-008, 2014.

  1. Signaling Adverse Drug Reactions with Novel Feature-based Similarity Model.

    Fan Yang, Xiaohui Yu, and George Karypis. IEEE Conf. on Bioinformatics and Biomedicine (BIBM), 2014.

  1. Personalized Multi-Regression Models for Predicting Students' Performance in Course Activities.

    Asmaa Elbadrawy, R. Scott Studham, and George Karypis. UMN CS 14-011, 2014.

  1. User-Specific Feature-based Similarity Models for Top-N Recommendation of New Items.

    Asmaa Elbadrawy and George Karypis. UMN CS 14-016, 2014.

  1. Big Data Frequent Pattern Mining.

    David C. Anastasiu, Jeremy Iverson, Shaden Smith, and George Karypis. Frequent Pattern Mining (editors: Charu C. Aggarwal and Jawei Han), Springer, 2014.

  1. Multi-threaded Modularity Based Graph Clustering using the Multilevel Paradigm.

    Dominique LaSalle and George Karypis. Journal of Parallel and Distributed Computing, 2014.