Categorical & Mixed Data Learning

Reading list of categorical, mixed data representation, clustering and anomaly detection

Review Papers

• Anomaly detection methods for categorical data: A review[J]. Taha A, Hadi A S, ACM Computing Surveys (CSUR), 2019

Representation & Similarity Metric

• Embedding-based Representation of Categorical Data by Hierarchical Value Coupling Learning, Songlei Jian, Longbing Cao, Guansong Pang, IJCAI2017
• Unsupervised Coupled Metric Similarity for Non-IID Categorical Data, Jian Songlei and Cao Longbing. TKDE2018
• CURE: Flexible Categorical Data Representation by Hierarchical Coupling Learning, Jian, Songlei and Cao, Longbing. TKDE2018

Clustering

• A fuzzy k-modes algorithm for clustering categorical data[J]. Huang Z, Ng M K. IEEE transactions on Fuzzy Systems. 1999
• CACTUS—clustering categorical data using summaries. Ganti V, Gehrke J, Ramakrishnan R. KDD1999
• Clicks: Mining subspace clusters in categorical data via k-partite maximal cliques. Zaki M J, Peters M. ICDE2005
• A novel attribute weighting algorithm for clustering high-dimensional categorical data[J]. Bai L, Liang J, Dang C, et al. Pattern Recognition, 2011
• Categorical data clustering: What similarity measure to recommend[J]. dos Santos T R L, Zárate L E. Expert Systems with Applications, 2015
• K-modes clustering algorithm for categorical data[J]. Sharma N, Gaud N. International Journal of Computer Applications, 2015

Anomaly Detection

• Fast and reliable anomaly detection in categorical data. Akoglu L, Tong H, Vreeken J, et al. CIKM2012
• Outlier Detection in Complex Categorical Data by Modelling the Feature Value Couplings, Guansong Pang, Longbing Cao. IJCAI2016
• Unsupervised Feature Selection for Outlier Detection by Modelling Hierarchical Value-Feature Couplings, Guansong Pang, Longbing Cao. ICDM2016
• Learning Homophily Couplings from Non-IID Data for Joint Feature Selection and Noise-Resilient Outlier Detection, Guansong Pang, Longbing Cao. IJCAI2017
• Selective Value Coupling Learning for Detecting Outliers in High-Dimensional Categorical Data, Guansong Pang, Hongzuo Xu, CIKM2017
• Exploring a high-quality outlying feature value set for noise-resilient outlier detection in categorical data. Xu H, Wang Y, Cheng L. CIKM2018
• Combine value clustering and weighted value coupling learning for outlier detection in categorical data. Xu H, Wang Y, Wu Z, et al. DEXA2018
• Embedding-Based Complex Feature Value Coupling Learning for Detecting Outliers in Non-IID Categorical Data, Hongzuo Xu, YongjunWang. AAAI2019
• MIX: A Joint Learning Framework for Detecting Both Clustered and Scattered Outliers in Mixed-Type Data, Hongzuo Xu, Yijie Wang. ICDM2019

High-dimensional Data

• Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection, Guansong Pang, Longbing Cao. KDD2018