Building the data warehouse (2nd ed.)
Building the data warehouse (2nd ed.)
Data mining solutions: methods and tools for solving real-world problems
Data mining solutions: methods and tools for solving real-world problems
Data preparation for data mining
Data preparation for data mining
A foundation for capturing and querying complex multidimensional data
Information Systems - Data warehousing
Extending the UML for Multidimensional Modeling
UML '02 Proceedings of the 5th International Conference on The Unified Modeling Language
Multidimensional Modeling with UML Package Diagrams
ER '02 Proceedings of the 21st International Conference on Conceptual Modeling
The involvement of human resources in large scale data mining projects
ISICT '03 Proceedings of the 1st international symposium on Information and communication technologies
If i had a model, i'd model in the mornin'
OOPSLA '04 Companion to the 19th annual ACM SIGPLAN conference on Object-oriented programming systems, languages, and applications
IEEE Transactions on Knowledge and Data Engineering
A UML profile for multidimensional modeling in data warehouses
Data & Knowledge Engineering - Special issue: ER 2003
Metrics for data warehouse conceptual models understandability
Information and Software Technology
A classification of stereotypes for object-oriented modeling languages
UML'99 Proceedings of the 2nd international conference on The unified modeling language: beyond the standard
Conceptual modeling for classification mining in data warehouses
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
Extending the UML for designing association rule mining models for data warehouses
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
Extending OCL for OLAP querying on conceptual multidimensional models of data warehouses
Information Sciences: an International Journal
Domain-specific language modelling with UML profiles by decoupling abstract and concrete syntaxes
Journal of Systems and Software
Enhancing the semantics of UML association redefinition
Data & Knowledge Engineering
RETRACTED: Model-driven development of OLAP metadata for relational data warehouses
Computer Standards & Interfaces
MIRABEL DW: managing complex energy data in a smart grid
DaWaK'12 Proceedings of the 14th international conference on Data Warehousing and Knowledge Discovery
Disease evolution visualization through historized versions of medical images
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
MDA-based visual modeling approach for resources link relationships using UML profile
Computer Standards & Interfaces
Information and Software Technology
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Time-series analysis is a powerful technique to discover patterns and trends in temporal data. However, the lack of a conceptual model for this data-mining technique forces analysts to deal with unstructured data. These data are represented at a low-level of abstraction and their management is expensive. Most analysts face up to two main problems: (i) the cleansing of the huge amount of potentially-analysable data and (ii) the correct definition of the data-mining algorithms to be employed. Owing to the fact that analysts' interests are also hidden in this scenario, it is not only difficult to prepare data, but also to discover which data is the most promising. Since their appearance, data warehouses have, therefore, proved to be a powerful repository of historical data for data-mining purposes. Moreover, their foundational modelling paradigm, such as, multidimensional modelling, is very similar to the problem domain. In this article, we propose a unified modelling language (UML) extension through UML profiles for data-mining. Specifically, the UML profile presented allows us to specify time-series analysis on top of the multidimensional models of data warehouses. Our extension provides analysts with an intuitive notation for time-series analysis which is independent of any specific data-mining tool or algorithm. In order to show its feasibility and ease of use, we apply it to the analysis of fish-captures in Alicante. We believe that a coherent conceptual modelling framework for data-mining assures a better and easier knowledge-discovery process on top of data warehouses.