Search results for "concept-drift"

Hits ?▲	Authors	Title	Venue	Year	Link	Author keywords
81	Chien-I Lee, Cheng-Jung Tsai, Jhe-Hao Wu, Wei-Pang Yang	A Decision Tree-Based Approach to Mining the Rules of Concept Drift.	FSKD (4)	2007	DBLP DOI BibTeX RDF
74	Fredrik Kilander, Carl Gustaf Jansson	COBBIT - A Control Procedure for COBWEB in the Presence of Concept Drift.	ECML	1993	DBLP DOI BibTeX RDF
74	Hila Becker, Marta Arias	Real-time ranking with concept drift using expert advice.	KDD	2007	DBLP DOI BibTeX RDF	data streams, ranking, online learning, concept drift
72	Joel Scanlan, Jacky Hartnett, Raymond Williams	DynamicWEB: Adapting to Concept Drift and Object Drift in COBWEB.	Australasian Conference on Artificial Intelligence	2008	DBLP DOI BibTeX RDF	Contextual Clustering, Data Mining, Concept Drift
69	João Gama 0001, Pedro Medas, Gladys Castillo, Pedro Pereira Rodrigues	Learning with Drift Detection.	SBIA	2004	DBLP DOI BibTeX RDF	Incremental Supervised Learning, Machine Learning, Concept Drift
69	Pei-Pei Li 0001, Xuegang Hu, Xindong Wu 0001	Mining Concept-Drifting Data Streams with Multiple Semi-Random Decision Trees.	ADMA	2008	DBLP DOI BibTeX RDF	Classification, Data Streams, Concept Drift, Random Decision Trees
68	Michaela M. Black, Ray J. Hickey	Learning classification rules for telecom customer call data under concept drift.	Soft Comput.	2003	DBLP DOI BibTeX RDF	Decision trees, User profiling, Concept drift, Adaptive learning
65	Indre Zliobaite	Expected Classification Error of the Euclidean Linear Classifier under Sudden Concept Drift.	FSKD (2)	2008	DBLP DOI BibTeX RDF
65	Hyun-Jun Kim, Jenu Shrestha, Heung-Nam Kim, GeunSik Jo	User Action Based Adaptive Learning with Weighted Bayesian Classification for Filtering Spam Mail.	Australian Conference on Artificial Intelligence	2006	DBLP DOI BibTeX RDF	Weighted Bayesian, Concept Drift, Adaptive Learning, Spam Filtering
60	Ryan Elwell, Robi Polikar	Incremental Learning of Variable Rate Concept Drift.	MCS	2009	DBLP DOI BibTeX RDF	nonstationary environment, Learn?+?+?.NSE, concept drift
59	Alexey Tsymbal, Mykola Pechenizkiy, Padraig Cunningham, Seppo Puuronen	Handling Local Concept Drift with Dynamic Integration of Classifiers: Domain of Antibiotic Resistance in Nosocomial Infections.	CBMS	2006	DBLP DOI BibTeX RDF
57	Kyosuke Nishida, Koichiro Yamauchi 0001	Detecting Concept Drift Using Statistical Testing.	Discovery Science	2007	DBLP DOI BibTeX RDF
55	João Gama 0001, Petr Kosina	Tracking Recurring Concepts with Meta-learners.	EPIA	2009	DBLP DOI BibTeX RDF	Recurring Concepts, Data Streams, Concept Drift
55	Matjaz Kukar	Drifting Concepts as Hidden Factors in Clinical Studies.	AIME	2003	DBLP DOI BibTeX RDF	partial memory learning, gradual forgetting, clinical studies, Data Mining, Machine Learning, windowing, concept drift
52	Eduardo Jaques Spinosa, André Carlos Ponce de Leon Ferreira de Carvalho, João Gama 0001	OLINDDA: a cluster-based approach for detecting novelty and concept drift in data streams.	SAC	2007	DBLP DOI BibTeX RDF	clustering, data streams, concept drift, novelty detection
52	George Forman	Tackling concept drift by temporal inductive transfer.	SIGIR	2006	DBLP DOI BibTeX RDF	machine learning, support vector machine, time series, text classification, concept drift, topic identification, inductive transfer
51	Antske Fokkens, Serge Ter Braake, Isa Maks, Davide Ceolin	On the Semantics of Concept Drift: Towards Formal Definitions of Concept Drift and Semantic Change.	Drift-a-LOD@EKAW	2016	DBLP BibTeX RDF
47	Dwi H. Widyantoro, John Yen	Relevant Data Expansion for Learning Concept Drift from Sparsely Labeled Data.	IEEE Trans. Knowl. Data Eng.	2005	DBLP DOI BibTeX RDF	relevance feedback, information filtering, Concept learning
45	Albert Bifet, Geoffrey Holmes 0001, Bernhard Pfahringer, Richard Kirkby, Ricard Gavaldà	New ensemble methods for evolving data streams.	KDD	2009	DBLP DOI BibTeX RDF	decision trees, data streams, concept drift, ensemble methods
45	Satoru Nishimura, Masahiro Terabe, Kazuo Hashimoto	Decision Tree Induction from Numeric Data Stream.	Australasian Conference on Artificial Intelligence	2008	DBLP DOI BibTeX RDF	Numeric Data Stream, Hoeffding Tree, Concept Drift
45	Yi Ding, Xue Li 0001, Maria E. Orlowska	Recency-based collaborative filtering.	ADC	2006	DBLP BibTeX RDF	item-based approach, recency-based approach, collaborative filtering, similarity measure, concept drift
43	João Gama 0001, Pedro Medas, Pedro Pereira Rodrigues	Learning decision trees from dynamic data streams.	SAC	2005	DBLP DOI BibTeX RDF
42	Sarah Jane Delany, Derek G. Bridge	Catching the Drift: Using Feature-Free Case-Based Reasoning for Spam Filtering.	ICCBR	2007	DBLP DOI BibTeX RDF
42	Leandro L. Minku, Allan P. White, Xin Yao 0001	The Impact of Diversity on Online Ensemble Learning in the Presence of Concept Drift.	IEEE Trans. Knowl. Data Eng.	2010	DBLP DOI BibTeX RDF	diversity, online learning, Concept drift, neural network ensembles
42	Federico Maggi, William K. Robertson, Christopher Krügel, Giovanni Vigna	Protecting a Moving Target: Addressing Web Application Concept Drift.	RAID	2009	DBLP DOI BibTeX RDF	Machine Learning, Anomaly Detection, Concept Drift, Web Application Security
42	Kevin B. Pratt, Gleb Tschapek	Visualizing concept drift.	KDD	2003	DBLP DOI BibTeX RDF	parallel coordinate graph, parallel histogram, visualization, concept drift, brushing
39	Stephen H. Bach, Marcus A. Maloof	Paired Learners for Concept Drift.	ICDM	2008	DBLP DOI BibTeX RDF
39	Carlos Pinto, João Gama 0001	Incremental discretization, application to data with concept drift.	SAC	2007	DBLP DOI BibTeX RDF
39	Michaela M. Black, Ray J. Hickey	Detecting and Adapting to Concept Drift in Bioinformatics.	KELSI	2004	DBLP DOI BibTeX RDF
39	Jeremy Z. Kolter, Marcus A. Maloof	Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift.	ICDM	2003	DBLP DOI BibTeX RDF
37	Yehuda Koren	Collaborative filtering with temporal dynamics.	KDD	2009	DBLP DOI BibTeX RDF	recommender systems, collaborative filtering, concept drift
37	Peng Wang 0027, Haixun Wang, Xiaochen Wu, Wei Wang 0009, Baile Shi	A Low-Granularity Classifier for Data Streams with Concept Drifts and Biased Class Distribution.	IEEE Trans. Knowl. Data Eng.	2007	DBLP DOI BibTeX RDF	Classification, association rule, data stream, concept drift
35	Michaela M. Black, Ray J. Hickey	Classification of Customer Call Data in the Presence of Concept Drift and Noise.	Soft-Ware	2002	DBLP DOI BibTeX RDF
35	Ray J. Hickey, Michaela M. Black	Refined Time Stamps for Concept Drift Detection During Mining for Classification Rules.	TSDM	2000	DBLP DOI BibTeX RDF
35	Bijan Raahemi, Weicai Zhong, Jing Liu 0006	Exploiting unlabeled data to improve peer-to-peer traffic classification using incremental tri-training method.	Peer-to-Peer Netw. Appl.	2009	DBLP DOI BibTeX RDF	Windowing technique, Tri-training, Peer-to-peer traffic, IP traffic identification, Concept drift, Unlabeled data, Stream data mining
35	Shohei Hido, Tsuyoshi Idé, Hisashi Kashima, Harunobu Kubo, Hirofumi Matsuzawa	Unsupervised Change Analysis Using Supervised Learning.	PAKDD	2008	DBLP DOI BibTeX RDF	two-sample test, concept drift, change analysis
35	Geoffrey I. Webb, Michael J. Pazzani, Daniel Billsus	Machine Learning for User Modeling.	User Model. User Adapt. Interact.	2001	DBLP DOI BibTeX RDF	machine learning, World Wide Web, computational complexity, user modeling, concept drift, information agents
34	Albert Bifet, Ricard Gavaldà	Adaptive Learning from Evolving Data Streams.	IDA	2009	DBLP DOI BibTeX RDF
34	Gladys Castillo, João Gama 0001, Pedro Medas	Adaptation to Drifting Concepts.	EPIA	2003	DBLP DOI BibTeX RDF
31	Nicola Fanizzi, Claudia d'Amato, Floriana Esposito	Conceptual Clustering and Its Application to Concept Drift and Novelty Detection.	ESWC	2008	DBLP DOI BibTeX RDF
31	John Case, Sanjay Jain 0001, Susanne Kaufmann, Arun Sharma 0001, Frank Stephan 0001	Predictive Learning Models for Concept Drift.	ALT	1998	DBLP DOI BibTeX RDF
30	Johannes Schmitt 0001, Matthias Hollick, Christoph Roos, Ralf Steinmetz	Adapting the User Context in Realtime: Tailoring Online Machine Learning Algorithms to Ambient Computing.	Mob. Networks Appl.	2008	DBLP DOI BibTeX RDF	machine learning, pervasive computing, context-aware computing, ambient computing
30	Seppo Puuronen, Mykola Pechenizkiy, Alexey Tsymbal	Effectiveness of Local Feature Selection in Ensemble Learning for Prediction of Antimicrobial Resistance.	CBMS	2008	DBLP DOI BibTeX RDF
30	Brent Wenerstrom, Christophe G. Giraud-Carrier	Temporal Data Mining in Dynamic Feature Spaces.	ICDM	2006	DBLP DOI BibTeX RDF
30	Manfred Klenner, Udo Hahn	Concept Versioning: A Methodology for Tracking Evolutionary Concept Drift in Dynamic Concept Systems.	ECAI	1994	DBLP BibTeX RDF
29	Jeremy Z. Kolter, Marcus A. Maloof	Using additive expert ensembles to cope with concept drift.	ICML	2005	DBLP DOI BibTeX RDF
27	Jinpeng Li, Hang Yu 0006, Zhenyu Zhang 0013, Xiangfeng Luo, Shaorong Xie	Concept Drift Adaptation by Exploiting Drift Type.	ACM Trans. Knowl. Discov. Data	2024	DBLP DOI BibTeX RDF
27	Tajwar Mehmood, Seemab Latif, Nor Shahida Mohd Jamail, Asad Malik 0001, Rabia Latif	LSTMDD: an optimized LSTM-based drift detector for concept drift in dynamic cloud computing.	PeerJ Comput. Sci.	2024	DBLP DOI BibTeX RDF
27	Vandana Bharti, Shabari S. Nair, Akshat Jain, Kaushal Kumar Shukla, Bhaskar Biswas	Concept drift detection in toxicology datasets using discriminative subgraph-based drift detector.	Briefings Bioinform.	2023	DBLP DOI BibTeX RDF
27	Arvind Kumar Gangwar, Sandeep Kumar 0004	Concept Drift in Software Defect Prediction: A Method for Detecting and Handling the Drift.	ACM Trans. Internet Techn.	2023	DBLP DOI BibTeX RDF
27	Firas Bayram, Bestoun S. Ahmed, Andreas Kassler	From Concept Drift to Model Degradation: An Overview on Performance-Aware Drift Detectors.	CoRR	2022	DBLP DOI BibTeX RDF
27	Firas Bayram, Bestoun S. Ahmed, Andreas Kassler	From concept drift to model degradation: An overview on performance-aware drift detectors.	Knowl. Based Syst.	2022	DBLP DOI BibTeX RDF
27	Ibnu Daqiqil Id, Masanobu Abe, Sunao Hara	Evaluation of concept drift adaptation for acoustic scene classifier based on Kernel Density Drift Detection and Combine Merge Gaussian Mixture Model.	CoRR	2021	DBLP BibTeX RDF
27	Anjin Liu, Jie Lu 0001, Guangquan Zhang 0001	Diverse Instance-Weighting Ensemble Based on Region Drift Disagreement for Concept Drift Adaptation.	IEEE Trans. Neural Networks Learn. Syst.	2021	DBLP DOI BibTeX RDF
27	Salvatore Greco, Tania Cerquitelli	Drift Lens: Real-time unsupervised Concept Drift detection by evaluating per-label embedding distributions.	ICDM (Workshops)	2021	DBLP DOI BibTeX RDF
27	Ivan A. Nikolov, Mark Philip Philipsen, Jinsong Liu, Jacob V. Dueholm, Anders Skaarup Johansen, Kamal Nasrollahi, Thomas B. Moeslund	Seasons in Drift: A Long Term Thermal Imaging Dataset for Studying Concept Drift.	NeurIPS Datasets and Benchmarks	2021	DBLP BibTeX RDF
27	Anjin Liu, Jie Lu 0001, Guangquan Zhang 0001	Diverse Instances-Weighting Ensemble based on Region Drift Disagreement for Concept Drift Adaptation.	CoRR	2020	DBLP BibTeX RDF
27	Zeng Li, Yan Xiong, Wenchao Huang	Drift-detection Based Incremental Ensemble for Reacting to Different Kinds of Concept Drift.	BigCom	2019	DBLP DOI BibTeX RDF
27	Robert Anderson 0001, Yun Sing Koh, Gillian Dobbie	Lift-Per-Drift: An Evaluation Metric for Classification Frameworks with Concept Drift Detection.	Australasian Conference on Artificial Intelligence	2018	DBLP DOI BibTeX RDF
27	Anjin Liu, Yiliao Song, Guangquan Zhang 0001, Jie Lu 0001	Regional Concept Drift Detection and Density Synchronized Drift Adaptation.	IJCAI	2017	DBLP DOI BibTeX RDF
27	Rodolfo C. Cavalcante, Adriano L. I. Oliveira	An approach to handle concept drift in financial time series based on Extreme Learning Machines and explicit Drift Detection.	IJCNN	2015	DBLP DOI BibTeX RDF
27	Indre Zliobaite	Combining Time and Space Similarity for Small Size Learning under Concept Drift.	ISMIS	2009	DBLP DOI BibTeX RDF
27	Ludmila I. Kuncheva, Indre Zliobaite	Linear Discriminant Classifier (LDC) for Streaming Data with Concept Drift.	SSPR/SPR	2008	DBLP DOI BibTeX RDF
27	José Ramón Méndez 0001, Florentino Fernández Riverola, Eva Lorenzo Iglesias, Fernando Díaz 0001, Juan M. Corchado	Tracking Concept Drift at Feature Selection Stage in SpamHunting: An Anti-spam Instance-Based Reasoning System.	ECCBR	2006	DBLP DOI BibTeX RDF
25	Ioannis Katakis 0001, Grigorios Tsoumakas, Evangelos Banos, Nick Bassiliades, Ioannis P. Vlahavas	An adaptive personalized news dissemination system.	J. Intell. Inf. Syst.	2009	DBLP DOI BibTeX RDF	News filtering, Dynamic feature space, Ontology, Personalization, Text classification, Concept drift
25	Angelos Stavrou, Gabriela F. Cretu-Ciocarlie, Michael E. Locasto, Salvatore J. Stolfo	Keep your friends close: the necessity for updating an anomaly sensor with legitimate environment changes.	AISec	2009	DBLP DOI BibTeX RDF	anomaly detection, concept drift, model update
25	Elena Ikonomovska, João Gama 0001, Raquel Sebastião, Dejan Gjorgjevikj	Regression Trees from Data Streams with Drift Detection.	Discovery Science	2009	DBLP DOI BibTeX RDF	data stream, change detection, concept drift, regression trees, stream data mining
25	Wei Qu, Yang Zhang 0010, Junping Zhu, Qiang Qiu	Mining Multi-label Concept-Drifting Data Streams Using Dynamic Classifier Ensemble.	ACML	2009	DBLP DOI BibTeX RDF	Binary Relevance, Dynamic Classifier Ensemble, Data Stream, Concept Drift, Multi-label
25	Pin Zhang, Juhua Pu, Yongli Liu, Zhang Xiong 0001	A Probabilistic Approach for Mining Drifting User Interest.	APWeb/WAIM	2009	DBLP DOI BibTeX RDF	Incremental Learning, Concept Drift, Interest Model
25	Jack Chongjie Xue, Gary M. Weiss	Quantification and semi-supervised classification methods for handling changes in class distribution.	KDD	2009	DBLP DOI BibTeX RDF	class distribution, classification, semi-supervised learning, concept drift, quantification
25	Pei-Pei Li 0001, Xuegang Hu, Qianhui Liang, Yunjun Gao	Concept Drifting Detection on Noisy Streaming Data in Random Ensemble Decision Trees.	MLDM	2009	DBLP DOI BibTeX RDF	Ensemble Decision Trees, Data Streams, Noise, Concept Drift
25	George Forman	Quantifying counts and costs via classification.	Data Min. Knowl. Discov.	2008	DBLP DOI BibTeX RDF	Prevalence estimation, Class distribution estimation, Quantification research methodology, Detecting and tracking trends, Classification, Text mining, Concept drift, Class imbalance, Supervised machine learning
25	Albert Bifet, Ricard Gavaldà	Mining adaptively frequent closed unlabeled rooted trees in data streams.	KDD	2008	DBLP DOI BibTeX RDF	closed mining, data streams, patterns, trees, concept drift
25	Satoru Nishimura, Masahiro Terabe, Kazuo Hashimoto, Koichiro Mihara	Learning Higher Accuracy Decision Trees from Concept Drifting Data Streams.	IEA/AIE	2008	DBLP DOI BibTeX RDF	CVFDT, decision tree, data stream, concept drift, naive-Bayes classifiers
25	Michael Muhlbaier, Robi Polikar	An Ensemble Approach for Incremental Learning in Nonstationary Environments.	MCS	2007	DBLP DOI BibTeX RDF	Nonstationary environment, Learn?+?+?.NSE, concept drift
25	Zoheir Sahel, Abdelhamid Bouchachia, Bogdan Gabrys, Paul Rogers	Adaptive Mechanisms for Classification Problems with Drifting Data.	KES (2)	2007	DBLP DOI BibTeX RDF	Incremental learning, Concept drift, adaptive classification
25	Haixun Wang, Jian Yin 0002, Jian Pei, Philip S. Yu, Jeffrey Xu Yu	Suppressing model overfitting in mining concept-drifting data streams.	KDD	2006	DBLP DOI BibTeX RDF	data streams, classifier, concept drift, classifier ensemble
25	Wei Fan 0001	Systematic data selection to mine concept-drifting data streams.	KDD	2004	DBLP DOI BibTeX RDF	decision trees, data streams, concept-drift
25	Tom Fawcett	"In vivo" spam filtering: a challenge problem for KDD.	SIGKDD Explor.	2003	DBLP DOI BibTeX RDF	challenge problems, class skew, data streams, text classification, spam, cost-sensitive learning, concept drift, imbalanced data
25	Haixun Wang, Wei Fan 0001, Philip S. Yu, Jiawei Han 0001	Mining concept-drifting data streams using ensemble classifiers.	KDD	2003	DBLP DOI BibTeX RDF	data streams, classifier, concept drift, classifier ensemble
25	Geoff Hulten, Laurie Spencer, Pedro M. Domingos	Mining time-changing data streams.	KDD	2001	DBLP DOI BibTeX RDF	Decision trees, data streams, incremental learning, concept drift, subsampling, Hoeffding bounds
23	Kutalmis Coskun, Borahan Tümer	Learning under concept drift and non-stationary noise: Introduction of the concept of persistence.	Eng. Appl. Artif. Intell.	2023	DBLP DOI BibTeX RDF
23	Xing Tian, Wing W. Y. Ng, Hui Wang 0001	Concept Preserving Hashing for Semantic Image Retrieval With Concept Drift.	IEEE Trans. Cybern.	2021	DBLP DOI BibTeX RDF
23	Xiulin Zheng, Peipei Li 0001, Xuegang Hu, Kui Yu	Semi-supervised classification on data streams with recurring concept drift and concept evolution.	Knowl. Based Syst.	2021	DBLP DOI BibTeX RDF
23	Oliver Becher, Laura Hollink, Desmond Elliott	Exploring Concept Representations for Concept Drift Detection.	SEMANTiCS (Workshops)	2017	DBLP BibTeX RDF
23	Saad Mohamad, Moamar Sayed Mouchaweh, Abdelhamid Bouchachia	Active Learning for Data Streams Under Concept Drift and Concept Evolution.	STREAMEVOLV@ECML-PKDD	2016	DBLP BibTeX RDF
23	Ahsanul Haque, Latifur Khan, Michael Baron, Bhavani Thuraisingham, Charu C. Aggarwal	Efficient handling of concept drift and concept evolution over Stream Data.	ICDE	2016	DBLP DOI BibTeX RDF
23	Yutaka Miyazaki, Yuzuru Tanaka	Concept Drift in documents and Formal Concept Analysis.	EJC	2009	DBLP DOI BibTeX RDF
22	Stefan Hoeglinger, Russel Pears, Yun Sing Koh	CBDT: A Concept Based Approach to Data Stream Mining.	PAKDD	2009	DBLP DOI BibTeX RDF
20	Mohammad M. Masud 0001, Jing Gao 0004, Latifur Khan, Jiawei Han 0001, Bhavani Thuraisingham	Integrating Novel Class Detection with Classification for Concept-Drifting Data Streams.	ECML/PKDD (2)	2009	DBLP DOI BibTeX RDF
20	Hoang Vu Nguyen, Vivekanand Gopalkrishnan, Praneeth Namburi	Online Outlier Detection Based on Relative Neighbourhood Dissimilarity.	WISE	2008	DBLP DOI BibTeX RDF
20	Zhenzheng Ouyang, Quanyuan Wu, Tao Wang	An Efficient Decision Tree Classification Method Based on Extended Hash Table for Data Streams Mining.	FSKD (5)	2008	DBLP DOI BibTeX RDF
20	Ludmila I. Kuncheva, Catrin O. Plumpton	Adaptive Learning Rate for Online Linear Discriminant Classifiers.	SSPR/SPR	2008	DBLP DOI BibTeX RDF
20	Fulufhelo V. Nelwamondo, Tshilidzi Marwala	Handling Missing Data from Heteroskedastic and Nonstationary Data.	ISNN (1)	2007	DBLP DOI BibTeX RDF
20	Gianluigi Folino, Clara Pizzuti, Giandomenico Spezzano	StreamGP: tracking evolving GP ensembles in distributed data streams using fractal dimension.	GECCO	2007	DBLP DOI BibTeX RDF	distributed streaming data, data mining, classification, genetic programming, ensemble
20	Sebastian Lühr, Mihai M. Lazarescu	A Visual Data Analysis Tool for Sport Player Performance Benchmarking, Comparison, and Change Detection.	ICTAI (1)	2007	DBLP DOI BibTeX RDF
20	Jan Ramon, Kurt Driessens, Tom Croonenborghs	Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling.	ECML	2007	DBLP DOI BibTeX RDF
20	Gladys Castillo, João Gama 0001	An Adaptive Prequential Learning Framework for Bayesian Network Classifiers.	PKDD	2006	DBLP DOI BibTeX RDF
20	Marlon Núñez, Raúl Fidalgo, Rafael Morales Bueno	On-Line Learning of Decision Trees in Problems with Unknown Dynamics.	MICAI	2005	DBLP DOI BibTeX RDF
20	Muhammad Fermi Pasha, Rahmat Budiarto, Mohammad Syukur, Masashi Yamada	EFIS: Evolvable-Neural-Based Fuzzy Inference System and Its Application for Adaptive Network Anomaly Detection.	ICMLC	2005	DBLP DOI BibTeX RDF