Abstract: Taste and smell classification from multilanguage descriptions can be performed by extracting, by one or more processors using natural language processing, a text including one or more words associated with taste and smell perceptions from an input received from a plurality of users. The input includes multilanguage information regarding at least one of changes in smell and changes in taste perceived by each of the plurality of users. Feature vectors are generated for the text extracted from the input using global vectors, and a distance between the feature vectors and a plurality of reference descriptors associated with taste and smell is calculated for determining a similarity between the text and the reference descriptors and creating a training dataset based on which a classification model is generated for categorizing the plurality of users according to the at least one of changes in smell and changes in taste.

Abstract: Taste and smell classification from multilanguage descriptions can be performed by extracting, by one or more processors using natural language processing, a text including one or more words associated with taste and smell perceptions from an input received from a plurality of users. The input includes multilanguage information regarding at least one of changes in smell and changes in taste perceived by each of the plurality of users. Feature vectors are generated for the text extracted from the input using global vectors, and a distance between the feature vectors and a plurality of reference descriptors associated with taste and smell is calculated for determining a similarity between the text and the reference descriptors and creating a training dataset based on which a classification model is generated for categorizing the plurality of users according to the at least one of changes in smell and changes in taste.

Abstract: A computing device may receive a text and parse the text into a syntactic tree. The computing device may determine binary relations and trinary relations within the plurality of node pairs and the plurality of node triples. The computing device may select a plurality of important node pairs and node triples from the plurality of node pairs and node triples. The computing device may calculate a plurality of probabilities within relations of the plurality of the important node pairs and the plurality of the important node triples. The computing device may calculate a plurality of statistics for the relations based on the calculated plurality of probabilities. The computing device may determine a score and a probability associated with the score using the calculated plurality of probabilities and the calculated plurality of statistics with a trained neural network, and may display the determined score and the determined probability.

Abstract: A cognitive system is provided for sorting of numeric values utilizing an identification of superlative adjectives. For a set of adjectives and a set of nouns identified from a corpus: using a first indication as to whether each adjective in a set of adjectives is to modify a term and a second indication as to whether each noun in the set of nouns is to modify each adjective in the set of adjectives, a third indication is determined of whether each noun in the set of nouns is to be modified by either a maximum or minimum superlative adjective and whether the third indication is greater than or equal to a predetermined threshold. If so, the adjective is added to a set of maximum or minimum superlative adjectives, which is then provided to the cognitive system for sorting of the numeric values.

Abstract: A cognitive system is provided for sorting of numeric values utilizing an identification of superlative adjectives. For a set of adjectives and a set of nouns identified from a corpus: using a first indication as to whether each adjective in a set of adjectives is to modify a term and a second indication as to whether each noun in the set of nouns is to modify each adjective in the set of adjectives, a third indication is determined of whether each noun in the set of nouns is to be modified by either a maximum or minimum superlative adjective and whether the third indication is greater than or equal to a predetermined threshold. If so, the adjective is added to a set of maximum or minimum superlative adjectives, which is then provided to the cognitive system for sorting of the numeric values.