Extracting keywords from budget transcripts using fuzzy logic

J.I. Sheeba and K. Vivekanandan

International Journal of Data Mining, Modelling and Management, 2016, vol. 8, issue 1, 62-74

Abstract: A keyword can be explained as the principal term that provides efficient access to the content in a document and it is also meant to be frequent occurrence of a particular word in the text which provides an effective meaning. This proposed framework is considered for extracting the important keywords from the given budget transcripts using fuzzy logic. Fuzzy logic helps to detect the keywords from the given budget meeting specified in the case of allocating number of funds, place, date, time, etc. Certain features are more important and rest of the portions have less meaning in order to have a balanced weight in computations, fuzzy logic is used to rectify this issue by defining membership function for each feature and output can be categorised into three sets like low and medium and high. Finally, the outputs are integrated by using fuzzy rules.

Keywords: data mining; text mining; keyword extraction; budget transcripts; fuzzy logic; keywords; fuzzy rules; budget meetings; fund allocation. (search for similar items in EconPapers)
Date: 2016
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