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International Journal of Data Mining & Knowledge Management Process (IJDKP)

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Editor:
AIRCC
ISSN:
2231-007X
Vistas:
24955
Seguidores:
1
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Solicitud de Artículos

International Journal of Data Mining & Knowledge Management Process (IJDKP) is an academic journal published by AIRCC. (ISSN 2231-007X).

International Journal of Data Mining & Knowledge Management Process (IJDKP) ISSN: 2230 - 9608[Online]; 2231 - 007X [Print] https://airccse.org/journal/ijdkp/ijdkp.html Call for Papers Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer- reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Topics of interest include, but are not limited to, the following Data Mining Foundations Theoretical Foundations of Data Mining Scalable, Parallel and Distributed Data Mining Mining Data Streams and Real Time Analytics Graph, Network and Heterogeneous Information Network Mining Graph Neural Networks, Graph Transformers and Dynamic Graph Learning Spatial, Temporal and Spatio Temporal Data Mining Text, Video, Audio and Multimedia Mining Web, Social Media and Hypergraph Mining Feature Engineering, Data Cleaning and Data Transformation Data Integration and Fusion Explainable Data Mining and Model Interpretability Privacy Preserving Data Mining, Differential Privacy and Federated Learning Adversarial Machine Learning and Robustness Interactive Mining, Visualization and Human in the Loop Analytics Automated Machine Learning (AutoML) and Neural Architecture Search Optimization Methods for Large Scale Data Mining Edge, IoT and Resource Constrained Data Mining Data Centric AI: Data Quality, Weak Supervision and Data Governance Foundation Models and Large Scale Pretrained Models for Data Mining Generative AI, Diffusion Models and Synthetic Data Generation Data Mining Applications Bioinformatics, Genomics and Computational Biology Healthcare, Medical Imaging and Clinical Decision Support Biometrics and Identity Analytics Financial Modeling, Fraud Detection and Risk Analytics Time Series Forecasting and Sequential Modeling Image, Video and Multimodal Analytics Cybersecurity, Intrusion Detection and Threat Intelligence Social Network Analysis and Social Computing Educational Data Mining and Learning Analytics E commerce, Recommender Systems and Personalization Smart Cities, Transportation and Urban Computing Environmental, Climate and Sustainability Analytics Scientific Machine Learning (Physics, Chemistry, Materials, Climate) Industrial, Manufacturing and IoT Data Mining Legal, Policy and Ethical Applications of Data Mining Human Behavior Modeling, Affective Computing and Behavioral Analytics Reinforcement Learning for Recommendation, Planning and Optimization Digital Twins, Simulation Driven Analytics and Synthetic EnvironmentsGeneration Knowledge Processing Data and Knowledge Representation Knowledge Graphs, Semantic Technologies and Knowledge Enhanced ML Knowledge Discovery Frameworks and Pipelines Pre and Post Processing in Knowledge Discovery Causal Inference, Causal Discovery and Counterfactual Reasoning Predictive Modeling, Evaluation and Model Validation Probabilistic and Statistical Methods for Knowledge Extraction Interactive Knowledge Exploration and Visualization Mining Trends, Emerging Patterns and Risk Analysis Knowledge Extraction from Noisy, Incomplete, or Low Quality Sources Hybrid AI Systems Combining Symbolic and Machine Learning Approaches Reasoning, Inference and Decision Support Systems Human Centered AI and User Driven Knowledge Discovery Trustworthy AI: Fairness, Accountability, Transparency and EthicsGeneration Systems, Infrastructure and Deployment ML Systems, Data Pipelines and MLOps Distributed Training and Inference Systems Hardware Aware Model Design and Acceleration Scalable Storage, Indexing and Retrieval for Data Mining Deployment, Monitoring and Lifecycle Management of Data Mining Models Paper submission Authors are invited to submit papers for this journal through e-mail [email protected] or [email protected] or [email protected]. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. Important Dates Submission Deadline : June 20, 2026 Notification                   : July 20, 2026 Final Manuscript Due : July 27, 2026 Publication Date         : Determined by the Editor-in-Chief For other details please visit: https://airccse.org/journal/ijdkp/ijdkp.html Contact Us: Here's where you can reach us [email protected] or [email protected] or [email protected] Submission Link: https://airccse.com/submissioncs/home.html Visit Our Other Journal: https://airccse.org/journal/ijwest/ijwest.html https://www.airccse.org/journal/ijgca/ijgca.html
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