This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Information Technology, FACULTY OF ENGINEERING, NATURAL AND MEDICAL SCIENCES, International Burch University , Sarajevo , Bosnia and Herzegovina
Information Technology, FACULTY OF ENGINEERING, NATURAL AND MEDICAL SCIENCES, International Burch University , Sarajevo , Bosnia and Herzegovina
Information Technology, FACULTY OF ENGINEERING, NATURAL AND MEDICAL SCIENCES, International Burch University , Sarajevo , Bosnia and Herzegovina
Modern data collection, storage, and processing rely on diverse techniques to handle various types of information, ranging from structured tables to free-form text. This paper explores the captivating application of Natural Language Processing (NLP) for categorizing titles from Google Forms or any other textual data. The process of training an NLP model will be demonstrated through a specific example. Just as we learn from our past experiences, NLP models need to be fed with relevant data and labels. This ensures accurate and efficient processing even when new titles are introduced. We will conclude with a fascinating demonstration of how NLP algorithms analyze the structure and meaning of titles. By identifying keywords and understanding the context, they can automatically classify titles into relevant categories. This dramatically simplifies data organization and analysis, empowering us to extract valuable insights faster.
The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.
