Open Science Research Excellence

ICKDDM 2019 : International Conference on Knowledge Discovery and Data Mining

Paris, France
December 30 - 31, 2019

Conference Code: 19FR12ICKDDM

Conference Proceedings

All submitted conference papers will be blind peer reviewed by three competent reviewers. The peer-reviewed conference proceedings are indexed in the Open Science Index, Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, and other index databases. Impact Factor Indicators.

Special Journal Issues

ICKDDM 2019 has teamed up with the Special Journal Issue on Knowledge Discovery and Data Mining. A number of selected high-impact full text papers will also be considered for the special journal issues. All submitted papers will have the opportunity to be considered for this Special Journal Issue. The paper selection will be carried out during the peer review process as well as at the conference presentation stage. Submitted papers must not be under consideration by any other journal or publication. The final decision for paper selection will be made based on peer review reports by the Guest Editors and the Editor-in-Chief jointly. Selected full-text papers will be published online free of charge.

Conference Sponsor and Exhibitor Opportunities

The Conference offers the opportunity to become a conference sponsor or exhibitor. To participate as a sponsor or exhibitor, please download and complete the Conference Sponsorship Request Form.

Important Dates

Abstracts/Full-Text Paper Submission Deadline   August 29, 2019
Notification of Acceptance/Rejection   September 10, 2019
Final Paper (Camera Ready) Submission & Early Bird Registration Deadline   November 29, 2019
Conference Dates   December 30 - 31, 2019

Important Notes

Please ensure your submission meets the conference's strict guidelines for accepting scholarly papers. Downloadable versions of the check list for Full-Text Papers and Abstract Papers.

Please refer to the Paper Submission GUIDE before submitting your paper.

Selected Conference Papers

1) Consumer Load Profile Determination with Entropy-Based K-Means Algorithm
Ioannis P. Panapakidis, Marios N. Moschakis
2) Localization of Geospatial Events and Hoax Prediction in the UFO Database
Harish Krishnamurthy, Anna Lafontant, Ren Yi
3) Comparison of Machine Learning Models for the Prediction of System Marginal Price of Greek Energy Market
Ioannis P. Panapakidis, Marios N. Moschakis
4) Deep Learning Based Fall Detection Using Simplified Human Posture
Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif
5) Predictive Semi-Empirical NOx Model for Diesel Engine
Saurabh Sharma, Yong Sun, Bruce Vernham
6) Using Textual Pre-Processing and Text Mining to Create Semantic Links
Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo
7) Maximization of Lifetime for Wireless Sensor Networks Based on Energy Efficient Clustering Algorithm
Frodouard Minani
8) Classification of Health Risk Factors to Predict the Risk of Falling in Older Adults
L. Lindsay, S. A. Coleman, D. Kerr, B. J. Taylor, A. Moorhead
9) A Mixing Matrix Estimation Algorithm for Speech Signals under the Under-Determined Blind Source Separation Model
Jing Wu, Wei Lv, Yibing Li, Yuanfan You
10) From Electroencephalogram to Epileptic Seizures Detection by Using Artificial Neural Networks
Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone
11) Performance Evaluation of Distributed Deep Learning Frameworks in Cloud Environment
Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang
12) Evaluating Machine Learning Techniques for Activity Classification in Smart Home Environments
Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard
13) Noise Reduction in Web Data: A Learning Approach Based on Dynamic User Interests
Julius Onyancha, Valentina Plekhanova
14) Missing Link Data Estimation with Recurrent Neural Network: An Application Using Speed Data of Daegu Metropolitan Area
JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim
15) Comparative Evaluation of Accuracy of Selected Machine Learning Classification Techniques for Diagnosis of Cancer: A Data Mining Approach
Rajvir Kaur, Jeewani Anupama Ginige

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