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Advisor(s)
Abstract(s)
Developing new services or improving existing ones is becoming more accessible with
the evolution of Natural Language Processing (NLP) techniques. Chatbots are a known
example of an NLP-based service; they can interact with humans using text messages or
natural language. NLP grants, however, the development of other types of services based
on natural languages, such as machine translation, email spam detection, information
extraction, content summarization, and question answering. A current need, to develop
smart cities projects, is a system that can match content (text) from a project offer
description with the candidates description by finding common patterns in different textual
descriptions. This project presents an implementation of an automated tool with AI and
NLP to match needs and concrete ideas for innovation with the skills and offers of the
business sector, including start-ups and entrepreneurs. In sentiment analysis, NLP can be
harnessed to recognize and categorize the emotional tone conveyed in textual content, such
as project collaborator reviews, customer reviews, or social media posts. The sentiment
analysis component in this project establishes a tool for comprehending and categorizing
sentiments, for candidates seeking engagement in smart cities projects.
Description
Keywords
Natural language processing nlp Content matching Smart cities Stemming and lemmatization Bag-of-words Bow Term frequency-inverse document frequency TFIDF TF IDF Stop words Cosine similarity Flask Sentiment analysis Polarity