Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper.
Query: An Efficient Approach to Detect Concept Drifts in Data Streams
Classification and Novel Class Detection in Concept-Drifting Data Streams under Time Constraints
Active Learning With Drifting Streaming Data
Exponentially Weighted Moving Average Charts for Detecting Concept Drift
Visualizing concept drift
The Problem of Concept Drift: Definitions and Related Work
Continuous outlier detection in data streams: an extensible framework and state-of-the-art algorithms
New ensemble methods for evolving data streams
Incremental Local Outlier Detection for Data Streams
Online anomaly detection with concept drift adaptation using recurrent neural networks
Cost-Sensitive Perceptron Decision Trees for Imbalanced Drifting Data Streams
Change detection in streaming data in the era of big data: models and issues
Modeling recurring concepts in data streams: a graph-based framework
A systematic evaluation approach for data stream-based applications
C-DenStream: Using Domain Knowledge on a Data Stream
Determining the Training Window for Small Sample Size Classification with Concept Drift
Nonparametric Detection of Anomalous Data Streams
An ensemble classification approach for handling spatio-temporal drifts in partially labeled data streams
Novelty detection algorithm for data streams multi-class problems
A Practical Approach to Classify Evolving Data Streams: Training with Limited Amount of Labeled Data
Distance-based Outlier Detection in Data Streams
A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based On Minimum Cuts
The Bacillus anthracis spore.
Analysing Social Networks Via the Internet
STRs vs. SNPs: thoughts on the future of forensic DNA testing.
The study and application of the IOT technology in agriculture