Authors:
Afef Walha
1
;
Faiza Ghozzi
2
and
Faïez Gargouri
2
Affiliations:
1
MIRACL Laboratory, Tunisia
;
2
MIRACL Laboratory and Institute of Computer Science and Multimedia, Tunisia
Keyword(s):
ETL, Social Data Warehouse, BPMN, Modeling, Topic Detection.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Business Process Management
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Domain Analysis and Modeling
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Health Engineering and Technology Applications
;
Knowledge Engineering and Ontology Development
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
Transforming social media data into meaningful and useful information to enable more effective decision-making is nowadays a hot topic for Social Business Intelligence (SBI) systems. Integrating such data into Social Data Warehouse (SDW) is in charge of ETL (Extraction, Transformation and Loading) which are the typical processes recognized as a complex combination of operations and technologies that consumes a significant portion of the DW development efforts. These processes become more complex when we consider the unstructured social sources. For that, we propose an ETL4Social modeling approach that designs ETL processes suitable to social data characteristics. This approach offers specific models to social ETL operations that help ETL designer to integrate data. A key role in the analysis of textual data is also played by topics, meant as specific concepts of interest within a subject area. In this paper, we mainly insist on emerging topic discovering models from textual media cli
ps. The proposed models are instantiated through Twitter case study. ETL4Social is considered a standard-based modeling approach using Business Process Modeling and Notation (BPMN). ETL Operations models are validated based on ETL4Social meta-model, which is an extension of BPMN meta-model.
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