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Recent advances on knowledge discovery and business intelligence
Author(s) -
Cortez Paulo,
Santos Manuel Filipe
Publication year - 2015
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/exsy.12087
Subject(s) - computer science , knowledge extraction , business intelligence , data science , domain knowledge , inference , big data , field (mathematics) , subject matter expert , knowledge base , knowledge management , expert system , data mining , artificial intelligence , mathematics , pure mathematics
Information Technology (IT) is advancing rapidly. In the last years, IT costs have reduced while data storage, communication and processing capabilities have increased. In effect, vast datasets are becoming commonplace. All this data hold valuable knowledge such as trends and patterns, which can be used to improve decision making and optimize chances of success. These datasets are often highly complex for a manual analysis due to the volume, variety and velocity properties of data. Following these advances, there has been a growing interest in using IT to provide useful knowledge, extracted from humans or raw data, for decision support. This interest was approached under different perspectives through the last decades [Carbonell et al., 1983, Ein-Dor and Segev, 1993, Turban et al., 2010, Piatetsky-Shapiro, 2011]: