Data warehouse and knowledge discovery

Auteurs

• A. Min Tjoa

Paramètres

• Informatique, programmation

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For over a decade, data warehousing and knowledge discovery technologies have become essential for decision-making in companies. Since 1999, the Data Warehousing and Knowledge Discovery (DaWaK) conference series has served as an international platform for practitioners and researchers to share findings, publish results, and engage in discussions on relevant research issues in these fields. The 7th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2005) continued this tradition, aiming to strike a logical balance between data warehousing and knowledge discovery. The conference featured papers addressing various unresolved research challenges in data warehousing, including ETL process modeling, integration issues, OLAP technology design from XML documents, and advancements in query processing and partitioning. In terms of data mining, topics covered included techniques, clustering, classification, and pattern recognition. The proceedings include technical papers selected for presentation at the conference. A total of 196 abstracts were submitted, resulting in 162 papers from 38 countries. The Program Committee ultimately selected 51 papers, yielding an acceptance rate of 31.4%.

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• Année de publication: 2005