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Heracles: A framework for developing and evaluating text mining algorithms

delete2019-08-01
delete6
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OA
AI
K
Kim Schouten
F
Flavius Frăsincar *
R
Rommert Dekker
M
Mark Riezebos
DOI:10.1016/j.eswa.2019.03.005delete
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Abstract

Abstract

En 中文
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. (C) 2019 Elsevier Ltd. All rights reserved.
Keywords:
Text mining
Algorithm evaluation
Research and development
Developers framework
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Journal

Expert Systems with Applications cover
Expert Systems with Applications
IF:
7.5
Papers:
3.0W
Citations:
10.2W

Organization

E
erasmus university rotterdam - excl erasmus mc
Scholars:
5.5K
Papers: 5.7K
Citations: 6
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