Albert Bifet | Academic Influence

Albert Bifet's AcademicInfluence.com Rankings

Albert Bifet

Computer Science

#7086

World Rank

#7463

Historical Rank

Big Data

#17

World Rank

#17

Historical Rank

Data Mining

#165

World Rank

#165

Historical Rank

Machine Learning

#2504

World Rank

#2537

Historical Rank

computer-science Degrees

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Computer Science

Albert Bifet's Degrees

PhD Computer Science University of Waikato
Masters Computer Science University of Porto
Bachelors Computer Science University of Porto

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Albert Bifet's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

A survey on concept drift adaptation (2014) (2112)
MOA: Massive Online Analysis (2010) (1414)
Learning from Time-Changing Data with Adaptive Windowing (2007) (1206)
Mining big data: current status, and forecast to the future (2013) (805)
Early Drift Detection Method (2005) (650)
Sentiment Knowledge Discovery in Twitter Streaming Data (2010) (645)
New ensemble methods for evolving data streams (2009) (596)
Adaptive random forests for evolving data stream classification (2017) (379)
A Survey on Ensemble Learning for Data Stream Classification (2017) (365)
Adaptive Learning from Evolving Data Streams (2009) (362)
Active Learning With Drifting Streaming Data (2014) (315)
Leveraging Bagging for Evolving Data Streams (2010) (289)
DATA STREAM MINING A Practical Approach (2009) (270)
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering (2010) (225)
Scikit-Multiflow: A Multi-output Streaming Framework (2018) (200)
SAMOA: scalable advanced massive online analysis (2015) (172)
Mining Big Data in Real Time (2013) (162)
Efficient Online Evaluation of Big Data Stream Classifiers (2015) (141)
Massive Online Analysis (2009) (135)
Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams (2010) (133)
Scalable and efficient multi-label classification for evolving data streams (2012) (126)
Machine learning for streaming data: state of the art, challenges, and opportunities (2019) (117)
Batch-Incremental versus Instance-Incremental Learning in Dynamic and Evolving Data (2012) (115)
Evaluation methods and decision theory for classification of streaming data with temporal dependence (2015) (112)
Spiking Neural Networks and Online Learning: An Overview and Perspectives (2019) (107)
Adaptive learning and mining for data streams and frequent patterns (2009) (98)
Next challenges for adaptive learning systems (2012) (96)
Fast Perceptron Decision Tree Learning from Evolving Data Streams (2010) (96)
An effective evaluation measure for clustering on evolving data streams (2011) (95)
Active Learning with Evolving Streaming Data (2011) (89)
Efficient data stream classification via probabilistic adaptive windows (2013) (85)
MACHINE LEARNING FOR DATA STREAMS (2018) (83)
Mining frequent closed graphs on evolving data streams (2011) (78)
Kalman Filters and Adaptive Windows for Learning in Data Streams (2006) (77)
Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them (2013) (76)
IoT Big Data Stream Mining (2016) (74)
Detecting Sentiment Change in Twitter Streaming Data (2011) (72)
Improving Adaptive Bagging Methods for Evolving Data Streams (2009) (72)
An Analysis of Factors Used in Search Engine Ranking (2005) (63)
River: machine learning for streaming data in Python (2020) (61)
Extremely Fast Decision Tree Mining for Evolving Data Streams (2017) (59)
Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking (2010) (59)
MOA-TweetReader: Real-Time Analysis in Twitter Streaming Data (2011) (53)
MOA: A Real-Time Analytics Open Source Framework (2011) (53)
STRIP: stream learning of influence probabilities (2013) (50)
Big Data Stream Learning with SAMOA (2014) (48)
Clustering Based Active Learning for Evolving Data Streams (2013) (48)
VHT: Vertical hoeffding tree (2016) (45)
On learning guarantees to unsupervised concept drift detection on data streams (2019) (43)
StreamDM: Advanced Data Mining in Spark Streaming (2015) (42)
CD-MOA: Change Detection Framework for Massive Online Analysis (2013) (38)
Streaming Random Patches for Evolving Data Stream Classification (2019) (37)
Mining adaptively frequent closed unlabeled rooted trees in data streams (2008) (36)
Data stream analysis: Foundations, major tasks and tools (2021) (35)
Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell Orders (2018) (34)
Multi-label Classification with Meta-Labels (2014) (34)
Ensembles of Restricted Hoeffding Trees (2012) (33)
On Dynamic Feature Weighting for Feature Drifting Data Streams (2016) (31)
Classifier Concept Drift Detection and the Illusion of Progress (2017) (31)
Drift Detection Using Stream Volatility (2015) (29)
MOA Concept Drift Active Learning Strategies for Streaming Data (2011) (29)
Deep learning in partially-labeled data streams (2015) (29)
Clustering Performance on Evolving Data Streams: Assessing Algorithms and Evaluation Measures within MOA (2010) (26)
A streaming flow-based technique for traffic classification applied to 12 + 1 years of Internet traffic (2016) (26)
Kaggle LSHTC4 Winning Solution (2014) (25)
Efficient multi-label classification for evolving data streams (2010) (25)
Adaptive random forests for data stream regression (2018) (24)
Distributed Adaptive Model Rules for mining big data streams (2014) (24)
Distributed Decision Tree Learning for Mining Big Data Streams (2013) (24)
Recurring Concept Meta-learning for Evolving Data Streams (2019) (24)
Mining frequent closed rooted trees (2009) (24)
Random Forests of Very Fast Decision Trees on GPU for Mining Evolving Big Data Streams (2014) (23)
FARF: A Fair and Adaptive Random Forests Classifier (2021) (22)
Merit-guided dynamic feature selection filter for data streams (2019) (21)
Adaptive Random Forests with Resampling for Imbalanced data Streams (2019) (21)
Stream Data Mining Using the MOA Framework (2012) (20)
Adaptive XGBoost for Evolving Data Streams (2020) (20)
FEAT: A Fairness-Enhancing and Concept-Adapting Decision Tree Classifier (2020) (20)
An efficient closed frequent itemset miner for the MOA stream mining system (2013) (20)
Inferring Demographics and Social Networks of Mobile Device Users on Campus From AP-Trajectories (2017) (19)
Data Stream Classification Using Random Feature Functions and Novel Method Combinations (2015) (19)
GNUsmail: Open Framework for On-line Email Classification (2010) (19)
Sampling informative patterns from large single networks (2020) (18)
Adaptive XML Tree Classification on Evolving Data Streams (2009) (18)
EXAD: A System for Explainable Anomaly Detection on Big Data Traces (2018) (18)
Streaming Multi-label Classification (2011) (17)
Efficient Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs (2017) (17)
Change detection in categorical evolving data streams (2014) (17)
Boosting decision stumps for dynamic feature selection on data streams (2019) (16)
Delayed labelling evaluation for data streams (2019) (16)
A Sketch-Based Naive Bayes Algorithms for Evolving Data Streams (2018) (15)
Incremental Ensemble Classifier Addressing Non-stationary Fast Data Streams (2014) (15)
Telemetry-based stream-learning of BGP anomalies (2018) (14)
Use of ensembles of Fourier spectra in capturing recurrent concepts in data streams (2015) (14)
A Survey on Spatio-temporal Data Analytics Systems (2021) (14)
Mining frequent closed trees in evolving data streams (2011) (13)
Binding data mining and expert knowledge for one-day-ahead prediction of hourly global solar radiation (2020) (13)
Mining Frequent Closed Unordered Trees Through Natural Representations (2007) (12)
Measuring the Shattering coefficient of Decision Tree models (2019) (12)
Large-Scale Learning from Data Streams with Apache SAMOA (2018) (12)
Low-latency multi-threaded ensemble learning for dynamic big data streams (2017) (11)
C-SMOTE: Continuous Synthetic Minority Oversampling for Evolving Data Streams (2020) (11)
Survey on Feature Transformation Techniques for Data Streams (2020) (11)
Using GNUsmail to Compare Data Stream Mining Methods for On-line Email Classification (2011) (11)
DyBED: An Efficient Algorithm for Updating Betweenness Centrality in Directed Dynamic Graphs (2018) (10)
A Survey on Semi-supervised Learning for Delayed Partially Labelled Data Streams (2021) (10)
Intersection Algorithms and a Closure Operator on Unordered Trees (2006) (10)
Data Stream Mining (2014) (10)
Subtree Testing and Closed Tree Mining Through Natural Representations (2007) (9)
Adaptive random forests for evolving data stream classification (2017) (9)
Analyzing and Repairing Concept Drift Adaptation in Data Stream Classification (2021) (8)
Recent trends in streaming data analysis, concept drift and analysis of dynamic data sets (2019) (8)
Correction to: Adaptive random forests for evolving data stream classification (2019) (8)
Unsupervised real-time detection of BGP anomalies leveraging high-rate and fine-grained telemetry data (2018) (7)
vertTIRP: Robust and efficient vertical frequent time interval-related pattern mining (2021) (7)
Efficient frequent subgraph mining on large streaming graphs (2019) (7)
Towards Automated Configuration of Stream Clustering Algorithms (2019) (7)
Mining Implications from Lattices of Closed Trees (2008) (7)
Discriminative Distance-Based Network Indices with Application to Link Prediction (2017) (7)
An In-depth Comparison of Group Betweenness Centrality Estimation Algorithms (2018) (7)
IDSA-IoT: An Intrusion Detection System Architecture for IoT Networks (2019) (7)
Learning Fast and Slow: A Unified Batch/Stream Framework (2018) (7)
Streaming Data Mining with Massive Online Analytics (MOA) (2018) (7)
Semi-supervised Learning over Streaming Data using MOA (2019) (6)
Adaptive Algorithms for Estimating Betweenness and k-path Centralities (2019) (6)
Incremental Rebalancing Learning on Evolving Data Streams (2020) (6)
Exploiting the stimuli encoding scheme of evolving Spiking Neural Networks for stream learning (2019) (6)
Metropolis-Hastings Algorithms for Estimating Betweenness Centrality (2019) (6)
Unsupervised Concept Drift Detection Using a Student-Teacher Approach (2020) (6)
Ensembles of Sparse Multinomial Classifiers for Scalable Text Classification (2012) (6)
confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms (2020) (6)
Studying and Exploiting the Relationship Between Model Accuracy and Explanation Quality (2021) (5)
ORSUM - Workshop on Online Recommender Systems and User Modeling (2020) (5)
Proceedings of the 2010 conference on Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams (2010) (5)
Arbitrated Dynamic Ensemble with Abstaining for Time-Series Forecasting on Data Streams (2019) (5)
CURIE: a cellular automaton for concept drift detection (2020) (5)
A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal (2022) (5)
Predicting over-indebtedness on batch and streaming data (2017) (5)
Predicting attributes and friends of mobile users from AP-Trajectories (2018) (5)
Improving parallel performance of ensemble learners for streaming data through data locality with mini-batching (2020) (5)
Scalable Distributed Real-Time Clustering for Big Data Streams (2013) (5)
ORSUM 2019 2nd workshop on online recommender systems and user modeling (2019) (5)
IoT data stream analytics (2020) (5)
IoT data stream analytics (2020) (5)
Improving the performance of bagging ensembles for data streams through mini-batching (2021) (5)
Machine Learning (In) Security: A Stream of Problems (2020) (5)
LP-ROBIN: Link prediction in dynamic networks exploiting incremental node embedding (2022) (4)
STUDD: A Student-Teacher Method for Unsupervised Concept Drift Detection (2021) (4)
Wangiri Fraud: Pattern Analysis and Machine-Learning-Based Detection (2023) (4)
Feature Scoring using Tree-Based Ensembles for Evolving Data Streams (2019) (4)
Real-Time Big Data Stream Analytics (2015) (4)
Droplet Ensemble Learning on Drifting Data Streams (2017) (4)
An eager splitting strategy for online decision trees in ensembles (2020) (4)
AutoML for Stream k-Nearest Neighbors Classification (2020) (3)
Benchmarking Stream Clustering Algorithms within the MOA Framework (2010) (3)
Scalable Model-Based Cascaded Imputation of Missing Data (2018) (3)
On Ensemble Techniques for Data Stream Regression (2020) (3)
Compressed k-Nearest Neighbors Ensembles for Evolving Data Streams (2020) (3)
Ubiquitous Artificial Intelligence and Dynamic Data Streams (2018) (3)
Introduction to the special issue on Big Data, IoT Streams and Heterogeneous Source Mining (2019) (3)
Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information (2021) (3)
Recurring concept memory management in data streams: exploiting data stream concept evolution to improve performance and transparency (2021) (3)
Streaming Time Series Forecasting using Multi-Target Regression with Dynamic Ensemble Selection (2020) (3)
Mining Internet of Things (IoT) Big Data Streams (2016) (3)
Incremental Mining of Frequent Serial Episodes Considering Multiple Occurrence (2022) (3)
Multi-label Classification (2014) (3)
Performance measures for evolving predictions under delayed labelling classification (2020) (2)
Closed and Maximal Tree Mining Using Natural Representations (2007) (2)
Challenges of Stream Learning for Predictive Maintenance in the Railway Sector (2020) (2)
Model Compression for Dynamic Forecast Combination (2021) (2)
Kaggle LSHTC 4 Winning Solution (2014) (2)
Proceedings, Part III, of the European Conference on Machine Learning and Knowledge Discovery in Databases - Volume 9286 (2015) (2)
Online Evaluation of Email Streaming Classifiers Using GNUsmail (2011) (2)
Adaptive Online Domain Incremental Continual Learning (2022) (2)
Emergent and Unspecified Behaviors in Streaming Decision Trees (2020) (2)
Resource-Aware Edge-Based Stream Analytics (2022) (2)
Metropolis-Hastings Algorithms for Estimating Betweenness Centrality in Large Networks (2017) (2)
Mining Big Data Streams with Apache SAMOA (2015) (2)
Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams (2020) (2)
Echo State Hoeffding Tree Learning (2016) (2)
CS-ARF: Compressed Adaptive Random Forests for Evolving Data Stream Classification (2020) (2)
Novel Adaptive Algorithms for Estimating Betweenness, Coverage and k-path Centralities (2018) (2)
Open challenges for Machine Learning based Early Decision-Making research (2022) (2)
Discriminative Streaming Network Embedding (2020) (2)
Combining Diverse Meta-Features to Accurately Identify Recurring Concept Drift in Data Streams (2023) (1)
Discriminative Distance-Based Network Indices and the Tiny-World Property (2017) (1)
Accurate Ensembles for Data Streams: Combining (2010) (1)
Autonomous HVAC Control, A Reinforcement Learning Approach (2018) (1)
Adaptive XML Tree Mining on Evolving Data Streams (2009) (1)
Balancing Performance and Energy Consumption of Bagging Ensembles for the Classification of Data Streams in Edge Computing (2022) (1)
Showcasing the TAIAO project: providing resources for machine learning from images of New Zealand's natural environment (2022) (1)
Randomizing the Self-Adjusting Memory for Enhanced Handling of Concept Drift (2020) (1)
XML Tree Classification on Evolving Data Streams (2012) (1)
VEPRECO: Vertical databases with pre-pruning strategies and common candidate selection policies to fasten sequential pattern mining (2022) (1)
Preventing Discriminatory Decision-making in Evolving Data Streams (2023) (1)
Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications (2012) (1)
11 Introduction to MOA and Its Ecosystem (2018) (1)
S2CE: a hybrid cloud and edge orchestrator for mining exascale distributed streams (2020) (1)
Learning from evolving data streams through ensembles of random patches (2021) (1)
Energy modeling of Hoeffding tree ensembles (2021) (1)
Deferral classification of evolving temporal dependent data streams (2016) (1)
Real-Time Machine Learning Competition on Data Streams at the IEEE Big Data 2019 (2019) (1)
Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part III (2015) (1)
5 Dealing with Change (2018) (1)
Online Hyperparameter Optimization for Streaming Neural Networks (2022) (1)
Proceedings of the 3rd International Conference on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications - Volume 36 (2014) (1)
S2CE (2021) (1)
TA4L: Efficient temporal abstraction of multivariate time series (2022) (1)
Rebalancing Learning on Evolving Data Streams (2019) (1)
Resource-aware Elastic Swap Random Forest for Evolving Data Streams (2019) (1)
Kalman Filtering for Learning with Evolving Data Streams (2021) (1)
ORSUM 2021 - 4th Workshop on Online Recommender Systems and User Modeling (2021) (1)
Linear tree shap (2022) (0)
NFA: A neural factorization autoencoder based online telephony fraud detection (2023) (0)
ORSUM 2022 - 5th Workshop on Online Recommender Systems and User Modeling (2022) (0)
AI Transformation in the Public Sector: Ongoing Research (2021) (0)
An eager splitting strategy for online decision trees in ensembles (2022) (0)
Session details: Theme: Information systems: DS - data streams track (2022) (0)
Analyzing Big Data Streams with Apache SAMOA (2015) (0)
Session details: Volume I: Artificial intelligence & agents, distributed systems, and information systems: data streams track (2013) (0)
Proceedings of the 4th Workshop on Online Recommender Systems and User Modeling -- ORSUM 2021 (2022) (0)
A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streams (2022) (0)
SOKNL: A novel way of integrating K-nearest neighbours with adaptive random forest regression for data streams (2022) (0)
Discriminative Distance-Based Network Indices, Link Prediction and the Tiny-World Property (2017) (0)
Towards time-evolving analytics: Online learning for time-dependent evolving data streams (2022) (0)
3 Hands-on Introduction to MOA (2018) (0)
Continuous Analytics of Web Streams (2019) (0)
Session details: Volume I: Artificial intelligence and agents, distributed systems, and information systems: Data streams track (2016) (0)
12 The Graphical User Interface (2018) (0)
Preface to the special issue on dynamic recommender systems and user models (2022) (0)
Fast Incremental Naïve Bayes with Kalman Filtering (2020) (0)
Proceedings of the Workshop on IoT Large Scale Learning from Data Streams co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18-22, 2017 (2017) (0)
Online Clustering: Algorithms, Evaluation, Metrics, Applications and Benchmarking (2022) (0)
A streaming flow-based technique for traffic classification applied to 12 + 1 years of Internet traffic (2015) (0)
Session details: Theme: Information systems: DS - Data streams track (2019) (0)
ChatGPT and Large Language Models: What are the Implications for Policy Makers? (2023) (0)
Network of Experts: Learning from Evolving Data Streams Through Network-Based Ensembles (2019) (0)
4 Streams and Sketches (2018) (0)
II STREAM MINING (2018) (0)
Learning Decision Trees Adaptively from Data Streams with Time Drift (2007) (0)
Session details: Volume I: Artificial intelligence and agents, distributed systems, and information systems: Data streams track (2014) (0)
Adaptive Model Compression of Ensembles for Evolving Data Streams Forecasting (2022) (0)
Data Stream Analytics (2023) (0)
Green Accelerated Hoeffding Tree (2022) (0)
Evaluation methods and decision theory for classification of streaming data with temporal dependence (2014) (0)
14 Using the API (2018) (0)
Fast and lightweight binary and multi-branch Hoeffding Tree Regressors (2021) (0)
Challenges of Machine Learning for Data Streams in the Banking Industry (2021) (0)
Continuous Health Monitoring of Machinery using Online Clustering on Unlabeled Data Streams (2022) (0)
Session details: Theme: Information systems: DS - Data streams track (2020) (0)
Linear TreeShap (2022) (0)
10 Frequent Pattern Mining (2018) (0)
Exploiting a Stimuli Encoding Scheme of Spiking Neural Networks for Stream Learning (2019) (0)
Deliverable D6.4.4 Applying episode mining and data stream mining to the tasks of evolving graphs and distributed Web search (2007) (0)
Confident Interpretations of Black Box Classifiers (2021) (0)
Editorial: Fifth special issue on Knowledge Discovery and Business Intelligence (2020) (0)
Session details: Theme: Information systems: DS - Data streams track (2021) (0)
Incremental k-Nearest Neighbors Using Reservoir Sampling for Data Streams (2021) (0)
Adaptive Neural Networks for Online Domain Incremental Continual Learning (2022) (0)
Assessing Vulnerability from Its Description (2022) (0)
Fifth special issue on knowledge discovery and business intelligence (2020) (0)
2 Big Data Stream Mining (2018) (0)
A Complete Streaming Pipeline for Real-time Monitoring and Predictive Maintenance (2021) (0)
Scalable and efficient multi-label classification for evolving data streams (2012) (0)
Evolution-Based Online Automated Machine Learning (2022) (0)
Correction to: Adaptive random forests for evolving data stream classification (2019) (0)
Stream2Graph: Dynamic Knowledge Graph for Online Learning Applied in Large-scale Network (2022) (0)
III THE MOA SOFTWARE (2018) (0)
Session details: Information systems: DS - data streams track (2018) (0)
Sketches for Time-Dependent Machine Learning (2021) (0)
StreamFlow: A System for Summarizing and Learning Over Industrial Big Data Streams (2022) (0)
Eﬀicient Batch-Incremental Classification Using UMAP for Evolving Data Streams (2022) (0)
SCALAR - A Platform for Real-time Machine Learning Competitions on Data Streams (2020) (0)

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