1384-5810

Data Mining and Knowledge Discovery （DATAMINE） - January 2020, 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 2020, issue 1
发布时间：
卷期年份： 2020
卷期官网： https://link.springer.com/journal/10618/volumes-and-issues/34-1
本期论文列表
A semi-supervised model for knowledge graph embedding

Interactive visual data exploration with subjective feedback: an information-theoretic approach

A drift detection method based on dynamic classifier selection

Topical network embedding

Grafting for combinatorial binary model using frequent itemset mining

A comparative study of data-dependent approaches without learning in measuring similarities of data objects

Matching code and law: achieving algorithmic fairness with optimal transport

Deep multi-task learning for individuals origin–destination matrices estimation from census data

FastEE: Fast Ensembles of Elastic Distances for time series classification

Guided sampling for large graphs

The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code

Counting frequent patterns in large labeled graphs: a hypergraph-based approach

Matrix profile goes MAD: variable-length motif and discord discovery in data series

struc2gauss: Structural role preserving network embedding via Gaussian embedding

An ultra-fast time series distance measure to allow data mining in more complex real-world deployments

TEAGS: time-aware text embedding approach to generate subgraphs

ABBA: adaptive Brownian bridge-based symbolic aggregation of time series

Efficient mining of the most significant patterns with permutation testing

A survey and benchmarking study of multitreatment uplift modeling

On normalization and algorithm selection for unsupervised outlier detection

SIAS-miner: mining subjectively interesting attributed subgraphs

Identifying exceptional (dis)agreement between groups

Mining relaxed functional dependencies from data

Parameterized low-rank binary matrix approximation

Integer programming ensemble of temporal relations classifiers

NegPSpan: efficient extraction of negative sequential patterns with embedding constraints

Relaxing the strong triadic closure problem for edge strength inference

MasterMovelets: discovering heterogeneous movelets for multiple aspect trajectory classification

Model-based exception mining for object-relational data

Robust and sparse multigroup classification by the optimal scoring approach

TS-CHIEF: a scalable and accurate forest algorithm for time series classification

An efficient K-means clustering algorithm for tall data

Discrete-time survival forests with Hellinger distance decision trees

Computing exact P-values for community detection

ptype: probabilistic type inference

ColluEagle: collusive review spammer detection using Markov random fields

Comparison of novelty detection methods for multispectral images in rover-based planetary exploration missions

Gaussian bandwidth selection for manifold learning and classification

Introducing time series snippets: a new primitive for summarizing long time series

Credible seed identification for large-scale structural network alignment

Visualizing image content to explain novel image discovery

Challenges in benchmarking stream learning algorithms with real-world data

MIDIA: exploring denoising autoencoders for missing data imputation

Bayesian mean-parameterized nonnegative binary matrix factorization

InceptionTime: Finding AlexNet for time series classification

DeepTable: a permutation invariant neural network for table orientation classification

Correction to: A unified view of density-based methods for semi-supervised clustering and classification

Introduction to the special issue of the ECML PKDD 2020 journal track

Delayed labelling evaluation for data streams

Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling

Fair-by-design matching

TEASER: early and accurate time series classification

Scalable attack on graph data by injecting vicious nodes

Treant: training evasion-aware decision trees

Large-scale network motif analysis using compression

ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels

Active learning for hierarchical multi-label classification

Deep soccer analytics: learning an action-value function for evaluating soccer players

Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations

CrawlSN: community-aware data acquisition with maximum willingness in online social networks