Authors:
Israel Griol-Barres
1
;
Sergio Milla
2
and
José Millet
3
Affiliations:
1
Instituto IDEAS, Vice-rectorate of Entrepreneurship and Employment, Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022, Valencia and Spain
;
2
FGYM, Vice-rectorate of Entrepreneurship and Employment, Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022, Valencia and Spain
;
3
Instituto ITACA, Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022, Valencia and Spain
Keyword(s):
Weak Signal of the Future, Business Intelligence Architecture, Unstructured Information, Text Mining, Decision-Making.
Related
Ontology
Subjects/Areas/Topics:
AI and Creativity
;
Artificial Intelligence
;
Data Mining
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Formal Methods
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Knowledge-Based Systems
;
Planning and Scheduling
;
Sensor Networks
;
Signal Processing
;
Simulation and Modeling
;
Soft Computing
;
Symbolic Systems
;
Uncertainty in AI
Abstract:
Not being able to cope with the constant changes in the market is currently one of the biggest threats for companies and start-ups. Therefore, the development of new systems to detect significant phenomena and future changes, is a key component for correct decision making that sets a correct course in the organisation. For this reason, a business intelligence architecture system is hereby proposed to allow the detection of discrete changes or weak signals in the present, indicative of more significant phenomena and transcendental changes in the future. In contrast to work currently available focusing on structured information sources, or at most with a single type of data source, the detection of these signals is here quantitatively based on heterogeneous and unstructured documents of various kinds (scientific journals, newspaper articles and social networks), to which text mining and natural language processing techniques (a multi-word expression analysis) are applied. The system ha
s been tested to study the future of solar panels and the artificial intelligence sectors, obtaining promising results to help business experts in the recognition of new driving factors of their markets and the development of new opportunities.
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