ERMIS: Extracting Knowledge from Unstructured Big Data for Supporting Business Decision Making - Artificial Intelligence Applications and Innovations Access content directly
Conference Papers Year : 2016

ERMIS: Extracting Knowledge from Unstructured Big Data for Supporting Business Decision Making

Abstract

Business managers support that decisions based on data analysis are better decisions. Nowadays, in the era of digital information, the accessible information sources are increasing rapidly, especially on the Internet. Also, the most critical information for business decisions is hidden in a large amount of unstructured data. Thus, Big Data analytics has become the cornerstone of modern Business Analytics providing insights for accurate decision making. ERMIS (Extensible pRoduct Monitoring by Indexing Social sources) system is able to aggregate unstructured and semi-structured data from different sources, process them and extracting knowledge by semantically annotating only the useful information. ERMIS Knowledge Base that is created from this process is a tool for supporting business decision making about a product.
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hal-01557616 , version 1 (06-07-2017)

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Konstantinos Arvanitis, Christos Alexakos, Andreas Papalambrou, Thomas Amorgianiotis, George Raptis, et al.. ERMIS: Extracting Knowledge from Unstructured Big Data for Supporting Business Decision Making. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. pp.611-622, ⟨10.1007/978-3-319-44944-9_54⟩. ⟨hal-01557616⟩
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