Many of today’s businesses are driven by data, and while traditionally only quantitative data is considered, the role of textual data in our digital world is rapidly increasing. Text mining allows to extract and aggregate numerical data from textual documents, which in turn can be used to improve key decision processes. In this paper, we propose Heracles, a framework for developing and evaluating text mining algorithms, with a broad range of applications in industry. In contrast to other frameworks, Heracles supports both the development and evaluation stages of text mining algorithms. A practical use case shows the versatility and ease-of-use of the proposed framework in the domain of aspect-based sentiment analysis.

Additional Metadata
Keywords Text mining, Algorithm evaluation, Research and development, Developers framework
Persistent URL dx.doi.org/10.1016/j.eswa.2019.03.005, hdl.handle.net/1765/119640
Journal Expert Systems with Applications
Citation
Schouten, K.I.M, Frasincar, F, Dekker, R, & Riezebos, M. (2019). Heracles: A Framework for Developing and Evaluating Text Mining Algorithms. Expert Systems with Applications, 127, 68–84. doi:10.1016/j.eswa.2019.03.005