Abstract
In this paper, we have discussed on applying text mining techniques to extract information on health benefits of medicinal plant from text article. The presence of multi-term phrases and complex sentences, i.e., the sentences that include clauses, implicit semantic relations in a text article, has always raised the complexity of information mining process. We have proposed a simple pattern-based semi-supervised approach powered by NLP techniques to deal with these issues. We have evaluated our methodology for a set of web documents on medicinal plants. Performance (in terms of recall) of our method was observed to considerably higher than existing relation extraction methodologies.
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Behera, N.K., Mahalakshmi, G.S. (2019). Medicinal Plant Information Extraction System—A Text Mining-Based Approach. In: Panigrahi, C., Pujari, A., Misra, S., Pati, B., Li, KC. (eds) Progress in Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 714. Springer, Singapore. https://doi.org/10.1007/978-981-13-0224-4_20
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DOI: https://doi.org/10.1007/978-981-13-0224-4_20
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