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Data Mining and Knowledge Discovery （DATAMINE） - January 2021, issue 1 论文列表

点击这里查看 Data Mining and Knowledge Discovery 的JCR分区、影响因子等信息
卷期号： January 2021, issue 1
发布时间：
卷期年份： 2021
卷期官网： https://link.springer.com/journal/10618/volumes-and-issues/35-1
本期论文列表
A survey of community detection methods in multilayer networks

A survey of deep network techniques all classifiers can adopt

Online summarization of dynamic graphs using subjective interestingness for sequential data

Recency-based sequential pattern mining in multiple event sequences

For real: a thorough look at numeric attributes in subgroup discovery

The network-untangling problem: from interactions to activity timelines

An exemplar-based clustering using efficient variational message passing

Natural language techniques supporting decision modelers

Mining explainable local and global subgraph patterns with surprising densities

SMILE: a feature-based temporal abstraction framework for event-interval sequence classification

Homophily outlier detection in non-IID categorical data

Mining full, inner and tail periodic patterns with perfect, imperfect and asynchronous periodicity simultaneously

Widening: using parallel resources to improve model quality

Streaming changepoint detection for transition matrices

Correction to: Streaming changepoint detection for transition matrices

Pseudoinverse graph convolutional networks

Fast computation of Katz index for efficient processing of link prediction queries

A deep multimodal model for bug localization

Extending greedy feature selection algorithms to multiple solutions

Efficient set-valued prediction in multi-class classification

Smoothed dilated convolutions for improved dense prediction

Relational Learning Analysis of Social Politics using Knowledge Graph Embedding

What’s in a name? – gender classification of names with character based machine learning models

Handling imbalance in hierarchical classification problems using local classifiers approaches

Correlations between random projections and the bivariate normal

An overlap sensitive neural network for class imbalanced data

CrashNet: an encoder–decoder architecture to predict crash test outcomes

Guest editorial: Special issue on mining for health

Adversarial balancing-based representation learning for causal effect inference with observational data

Affinity analysis for studying physicians’ prescription behavior.

Feature extraction from unequal length heterogeneous EHR time series via dynamic time warping and tensor decomposition

Predictive modeling of infant mortality

The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances

Detecting singleton spams in reviews via learning deep anomalous temporal aspect-sentiment patterns

Variational auto-encoder based Bayesian Poisson tensor factorization for sparse and imbalanced count data

Social explorative attention based recommendation for content distribution platforms

User preference and embedding learning with implicit feedback for recommender systems

A framework for deep constrained clustering

Learning tractable probabilistic models for moral responsibility and blame

Mining communities and their descriptions on attributed graphs: a survey

Deep graph similarity learning: a survey

Detecting virtual concept drift of regressors without ground truth values

ForestDSH: a universal hash design for discrete probability distributions

Recurring concept memory management in data streams: exploiting data stream concept evolution to improve performance and transparency

FuseRec: fusing user and item homophily modeling with temporal recommender systems

Time series motifs discovery under DTW allows more robust discovery of conserved structure

Word-class embeddings for multiclass text classification

Dataset2Vec: learning dataset meta-features

Sparse randomized shortest paths routing with Tsallis divergence regularization

Time series extrinsic regression

Multi-label learning with missing and completely unobserved labels

Sequential recommendation with metric models based on frequent sequences

Tackling ordinal regression problem for heterogeneous data: sparse and deep multi-task learning approaches

Boosting house price predictions using geo-spatial network embedding

Social media as author-audience games

Isolation kernel: the X factor in efficient and effective large scale online kernel learning

Implicit consensus clustering from multiple graphs

A Lagrangian-based score for assessing the quality of pairwise constraints in semi-supervised clustering

Time series clustering in linear time complexity

Chebyshev approaches for imbalanced data streams regression models

Continuous treatment effect estimation via generative adversarial de-confounding

Characterizing attitudinal network graphs through frustration cloud

Introduction to the special issue of the ECML PKDD 2021 journal track

BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descent

Early abandoning and pruning for elastic distances including dynamic time warping

MultiETSC: automated machine learning for early time series classification

CURIE: a cellular automaton for concept drift detection

VFC-SMOTE: very fast continuous synthetic minority oversampling for evolving data streams

Unsupervised domain adaptation with non-stochastic missing data

Effective social post classifiers on top of search interfaces

Fake review detection on online E-commerce platforms: a systematic literature review

AURORA: A Unified fRamework fOR Anomaly detection on multivariate time series

Hyperbolic node embedding for temporal networks

TSK-Streams: learning TSK fuzzy systems for regression on data streams

An alternating nonmonotone projected Barzilai–Borwein algorithm of nonnegative factorization of big matrices

Data-driven detection of counterpressing in professional football

Differentially Private Distance Learning in Categorical Data

Structure learning for relational logistic regression: an ensemble approach

Attention based adversarially regularized learning for network embedding

Selego: robust variate selection for accurate time series forecasting

Link prediction in dynamic networks using random dot product graphs

K-plex cover pooling for graph neural networks