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Develop Sentiment Analysis Model: The primary responsibility is to develop a sentiment analysismodel. This model should be capable of predicting emotions from text data. It involves natural language processing (NLP) techniques and machine learning SVM..
Text Classification: Classify the text data from EDOM ( dataset or source of textual information) into one of the five predefined emotion categories: very good, good, enough, less, and unknown. This classification based on the sentiment and context of the text.
Integration with Flask Web: Integrate the developed sentiment analysis model into a Flask web application.
Emotion Determination: Implement the logic to determine emotions by analyzing the content of the text.
Article Publication: Publish articles or research findings related to the sentiment analysis model and its applications to the Directorate General of Intellectual Property (Dirjen HKI).
Developed and maintained responsive and user-friendly websites using Flask, HTML, CSS, JavaScript and FlaskSQLAlchemy.