Knowledge And Information Systems（KAIS ）的APRIL 2019, ISSUE 1论文列表

卷期号： April 2019, issue 1

发布时间：

卷期年份： 2019

卷期官网： https://link.springer.com/journal/10115/volumes-and-issues/59-1

Fast detection of community structures using graph traversal in social networks

DIS-C: conceptual distance in ontologies, a graph-based approach

Fast crawling methods of exploring content distributed over large graphs

Multi-label classification using stacked hierarchical Dirichlet processes with reduced sampling complexity

A large margin time series nearest neighbour classification under locally weighted time warps

A comprehensive empirical comparison of hubness reduction in high-dimensional spaces

Expert deduction rules in data mining with association rules: a case study

A smoothed monotonic regression via L2 regularization

RTCRelief-F: an effective clustering and ordering-based ensemble pruning algorithm for facial expression recognition

TensorCast: forecasting and mining with coupled tensors

Preferences-based learning of multinomial logit model

An active learning-based approach for location-aware acquaintance inference

Dynamic skyline computation on massive data

Instance reduction for one-class classification

Who should I invite: predicting event participants for a host user

A hybrid isotonic separation training algorithm with correlation-based isotonic feature selection for binary classification

Self-taught support vector machines

Query-dependent learning to rank for cross-lingual information retrieval

Split miner: automated discovery of accurate and simple business process models from event logs

A novel density peaks clustering with sensitivity of local density and density-adaptive metric

\(\hbox {NE}^2\): named event extraction engine

DMHUPS: Discovering Multiple High Utility Patterns Simultaneously

Self-learning and embedding based entity alignment

A probabilistic model for semantic advertising

Sentiment analysis using semantic similarity and Hadoop MapReduce

An innovative linear unsupervised space adjustment by keeping low-level spatial data structure

A new truth discovery method for resolving object conflicts over Linked Data with scale-free property