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A Research Review and Taxonomy Development for Decision Support and Business Analytics Using Semantic Text Mining

Kő, Andrea and Gillani, Saira (2020) A Research Review and Taxonomy Development for Decision Support and Business Analytics Using Semantic Text Mining. International Journal of Information Technology & Decision Making, 19 (1). pp. 97-126. DOI http://doi.org/10.1142/S0219622019300076

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Official URL: http://doi.org/10.1142/S0219622019300076


Abstract

By 2018, business analytics (BA), believed by global CIOs to be of strategic importance, had for years been their top priority. It is also a focus of academic research, as shown by a large number of papers, books, and research reports. On the other hand, the BA domain su®ers from several incorrect, imprecise, and incomplete notions. New areas and concepts emerge quickly; making it di±cult to ascertain their structure. BA-related taxonomies play a crucial role in analyzing, classifying, and understanding related objects. However, according to the literature on taxonomy development in information systems (IS), in most cases the process is ad hoc. BA taxonomies and frameworks are available in the literature; however, some are excessively general frameworks with a high-level conceptual focus, while others are application or domain-speci¯c. Our paper aims to present a novel semi-automatic method for taxonomy development and maintenance in the ¯eld of BA using content analysis and text mining. The contribution of our research is threefold: (1) the taxonomy development method, (2) the draft taxonomy for BA, and (3) identifying the latest research areas and trends in BA.

Item Type:Article
Uncontrolled Keywords:taxonomy, taxonomy development, business analytics, text mining, semantic technology, ontology
Subjects:Economic development
Computer science
DOI:http://doi.org/10.1142/S0219622019300076
ID Code:6077
Deposited By: MTMT SWORD
Deposited On:20 Nov 2020 16:31
Last Modified:20 Nov 2020 16:32

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