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 suffers from several incorrect, imprecise, and incomplete notions. New areas and concepts emerge quickly; making it difficult 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-specific. Our paper aims to present a novel semi-automatic method for taxonomy development and maintenance in the field 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.

中文翻译：

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使用语义文本挖掘的决策支持和业务分析的研究回顾和分类发展

到 2018 年，被全球 CIO 认为具有战略重要性的业务分析 (BA) 多年来一直是他们的首要任务。大量的论文、书籍和研究报告表明，它也是学术研究的重点。另一方面，BA 领域存在几个不正确、不精确和不完整的概念。新的领域和概念迅速出现；很难确定它们的结构。与 BA 相关的分类法在分析、分类和理解相关对象方面起着至关重要的作用。然而，根据有关信息系统 (IS) 分类发展的文献，在大多数情况下，该过程是临时的。文学学士分类法和框架可在文献中找到；然而，有些是过于笼统的框架，具有高层次的概念焦点，而另一些则是应用程序或特定领域的。我们的论文旨在提出一种使用内容分析和文本挖掘在 BA 领域进行分类开发和维护的新型半自动方法。我们研究的贡献有三个：（1）分类法开发方法，（2）BA分类法草案，以及（3）确定BA的最新研究领域和趋势。