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Erschienen in:
2020 | OriginalPaper | Buchkapitel
A Design and an Implementation of Forecast Sentence Extractor
verfasst von : Benyatip Srichareon, Suparerk Manitpornsut, Prapas Pongdamrong
Erschienen in: Data Communication and Networks
Verlag: Springer Singapore
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Abstract
Strategic planning is a practical approach for researchers to conduct the STEEP analysis. One of the most promising approaches for strategic planning is the Foresight Framework. In the very first steps of Foresight Framework, however, the environmental scanning is involved. This process is time-consumed since a very large amount of data must be explored. To alleviate the time in such a process, this study proposes a design and an implementation of the forecast sentence extractor by using natural language processing and machine learning algorithm. The proposed algorithm digests a long article and then provides a short list of forecast sentences. Three feature selection approaches are tested. From the experimental studies, the accuracy of the proposed algorithm is up to 85.10%.