Open AccessNatural Language Processing through the Subtractive Mountain Clustering Algorithm - A Medication Intake Chatbot
Author(s) -
Paulo Salgado,
T-P Azevedo Perdicoúlis
Publication year - 2021
Publication title -
international journal on natural language computing (print)/international journal on natural language computing
Language(s) - English
Resource type - Journals
eISSN - 2319-4111
pISSN - 2278-1307
DOI - 10.5121/ijnlc.2021.10503
Subject(s) - chatbot , computer science , cluster analysis , set (abstract data type) , metric (unit) , population , artificial intelligence , data mining , natural language processing , information retrieval , algorithm , medicine , engineering , programming language , operations management , environmental health
In this work, the subtractive mountain clustering algorithm has been adapted to the problem of natural languages processing in view to construct a chatbot that answers questions posed by the user. The implemented algorithm version allosws for the association of a set of words into clusters. After finding the centre of every cluster — the most relevant word, all the others are aggregated according to a defined metric adapted to the language processing realm. All the relevant stored information (necessary to answer the questions) is processed, as well as the questions, by the algorithm. The correct processing of the text enables the chatbot to produce answers that relate to the posed queries. Since we have in view a chatbot to help elder people with medication, to validate the method, we use the package insert of a drug as the available information and formulate associated questions. Errors in medication intake among elderly people are very common. One of the main causes for this is their loss of ability to retain information. The high amount of medicine intake required by the advanced age is another limiting factor. Thence, the design of an interactive aid system, preferably using natural language, to help the older population with medication is in demand. A chatbot based on a subtractive cluster algorithm is the chosen solution.