A5087405585- Advanced Database Systems and Queries
- Semantic Web and Ontologies
- Data Quality and Management
- Data Management and Algorithms
- Service-Oriented Architecture and Web Services
- Cloud Computing and Resource Management
- Big Data and Business Intelligence
- Scientific Computing and Data Management
- Business Process Modeling and Analysis
- Data Mining Algorithms and Applications
- Machine Learning and Data Classification
- Data Stream Mining Techniques
- Software System Performance and Reliability
- Software Engineering Research
- E-Learning and Knowledge Management
- Advanced Data Storage Technologies
- Advanced Software Engineering Methodologies
- Imbalanced Data Classification Techniques
- Intelligent Tutoring Systems and Adaptive Learning
- Open Education and E-Learning
- Higher Education Teaching and Evaluation
- Digital Imaging for Blood Diseases
- IoT and Edge/Fog Computing
- Distributed and Parallel Computing Systems
- Smart Grid Energy Management
Universitat Politècnica de Catalunya
2015-2024
Hasselt University
2021
University of Ioannina
2021
Centre Hospitalier de Béziers
2020
Universidad de Granada
2002
University of California, Irvine
1994
Multidimensional modeling requires specialized design techniques. Though a lot has been written about how data warehouse should be designed, there is no consensus on method yet. This paper follows from wide discussion that took place in Dagstuhl, during the Perspectives Workshop "Data Warehousing at Crossroads", and aimed outlining some open issues of warehouses. More precisely, regarding conceptual models, logical methods for design, interoperability, new architectures applications are considered.
This paper describes the convergence of some most influential technologies in last few years, namely data warehousing (DW), on-line analytical processing (OLAP), and Semantic Web (SW). OLAP is used by enterprises to derive important business-critical knowledge from inside company. However, interesting queries can no longer be answered on internal alone, external must also discovered (most often web), acquired, integrated, (analytically) queried, resulting a new type OLAP, exploratory OLAP....
Self-service business intelligence is about enabling non-expert users to make well-informed decisions by enriching the decision process with situational data, i.e., data that have a narrow focus on specific problem and, typically, short lifespan for small group of users. Often, these are not owned and controlled maker; their search, extraction, integration, storage reuse or sharing should be accomplished makers without any intervention designers programmers. The goal this paper present...
Many methodologies have been presented to support the multidimensional design of data warehouse. First introduced were requirement-driven but semantics a warehouse require also consider sources along process. In following years, gained relevance in modeling and gave rise several data-driven that automate process from relational sources. Currently, research on is still hot topic we two main lines. On one hand, new hybrid automatic proposing combine approaches. other approaches focus...
This paper presents a new approach to automate the multidimensional design of Data Warehouses. In our we propose semi-automatable method aimed find business concepts from domain ontology representing different and potentially heterogeneous data sources domain.In short, identifies having nothing in common but that they are all described by an ontology.
Context: Software evolution ensures that software systems in use stay up to date and provide value for end-users. However, it is challenging requirements engineers continuously elicit needs used by heterogeneous end-users who are out of organisational reach. Objective: We aim at supporting continuous elicitation combining user feedback usage monitoring. Online mechanisms enable remotely communicate problems, experiences, opinions, while monitoring provides valuable information about runtime...
Abstract The demand for performing data analysis is steadily rising. As a consequence, people of different profiles (i.e., nonexperienced users) have started to analyze their data. However, this challenging them. A key step that poses difficulties and determines the success mining (model/algorithm selection problem). Meta-learning technique used assisting non-expert users in step. effectiveness meta-learning is, however, largely dependent on description/characterization datasets...
This paper presents a multidimensional conceptual object-oriented model, its structures, integrity constraints and query operations. It has been developed as an extension of UML core metaclasses to facilitate usage, well avoid the introduction completely new concepts. YAM/sup 2/ allows representation several semantically related star schemas, summarizability identification constraints.
There is currently a burst of Big Data (BD) processed and stored in huge raw data repositories, commonly called Lakes (DL). These BD require new techniques integration schema alignment order to make the usable by its consumers discover relationships linking their content. This can be provided metadata services which describe However, there lack systematic approach for such kind discovery management. Thus, we propose framework profiling informational content DL, call information profiling....
In the last years, problems of using generic storage techniques for very specific applications has been detected and outlined. Thus, some alternatives to relational DBMSs (e.g., BigTable) are blooming. On other hand, cloud computing is already a reality that helps save money by eliminating hardware as well software fixed costs just pay per use. Indeed, tools exploit also here. The trend in this case toward based on MapReduce paradigm developed Google. paper, we explore possibility having...