The mining method of trigger word for food nutrition matching Online publication date: Thu, 26-Nov-2020
by Guangli Zhu; Qiaoyun Wang; Hanran Liu; Shunxiang Zhang
International Journal of Computational Science and Engineering (IJCSE), Vol. 23, No. 3, 2020
Abstract: The trigger words related to food nutrition matching have an effect on classifying the rational food nutrition matching. This paper proposes a trigger word localisation method for food nutrition matching. First, food information frequency vector can be extracted by the number of food names, the number of nutrition ingredients and the number of matching effects in the sentence. The sentences unrelated to food nutrition matching can be filtered. Then, the two food verb-noun joint probability matrices can be constructed. By comparing row mean value of the two matrices, whether the verb is a trigger word can be judged. Lastly, under the premise of commendatory and derogatory probabilities of the trigger word, the food nutrition matching can be classified as two types by Naive Bayes. The experiments show that proposed method in this paper effectively detects the trigger word related to food nutrition matching.
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