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ORCIDInternational Journal of Data Warehousing and Mining, Volume 15
Volume 15, Number 1, 2019
- Ibtisam Ferrahi, Sandro Bimonte, Kamel Boukhalfa
:
Logical and Physical Design of Spatial Non-Strict Hierarchies in Relational Spatial Data Warehouse. 1-18 - Toshihiro Osaragi:
Classification and Space Cluster for Visualizing GeoInformation. 19-38 - Sulan Zhang, Jiaqiang Wan:
Anomaly Region Detection Based on DMST. 39-57 - P. Lalitha Kumari, S. G. Sanjeevi, Madhusudhana Rao T. V.:
Mining Top-k Regular High-Utility Itemsets in Transactional Databases. 58-79
Volume 15, Number 2, 2019
- Sandro Bimonte, Omar Boussaid, Michel Schneider, Fabien Ruelle:
Design and Implementation of Active Stream Data Warehouses. 1-21 - Olfa Layouni, Jalel Akaichi:
Spatio-Temporal OLAP Queries Similarity Measure and Algorithm. 22-41 - Jakub Szkandera, Ondrej Kaas, Ivana Kolingerová:
A Clustering Approach to Path Planning for Big Groups. 42-61 - Josephine M. Namayanja, Vandana P. Janeja:
Change Detection in Large Evolving Networks. 62-79
Volume 15, Number 3, 2019
- Kuldeep Singh:
Efficient Algorithm for Mining High Utility Pattern Considering Length Constraints. 1-27 - Selen Yilmaz Isikhan, Erdem Karabulut, Afshin Samadi, Saadettin Kiliçkap:
Adaptation of Error Adjusted Bagging Method for Prediction. 28-45 - Canan Eren Atay, Georgia Garani:
Maintaining Dimension's History in Data Warehouses Effectively. 46-62 - Haitao Zhang, Yunhong Zhu:
A Method of Sanitizing Privacy-Sensitive Sequence Pattern Networks Mined From Trajectories Released. 63-89
Volume 15, Number 4, 2019
- Mikolaj Markiewicz, Jakub Koperwas:
Hybrid Partitioning-Density Algorithm for K-Means Clustering of Distributed Data Utilizing OPTICS. 1-20 - Conor Gallagher, Eoghan Furey, Kevin Curran:
The Application of Sentiment Analysis and Text Analytics to Customer Experience Reviews to Understand What Customers Are Really Saying. 21-47 - Samson Oni, Zhiyuan Chen, Susan Hoban, Onimi Jademi:
A Comparative Study of Data Cleaning Tools. 48-65 - Satoshi Hiai, Kazutaka Shimada:
Sarcasm Detection Using RNN with Relation Vector. 66-78
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