Tag Suggestion System Using Multi-Label Text Categorization

Tag Suggestion System Using Multi-Label Text Categorization

JOSHITHA¹, Dr. DURGESH KUMAR²

¹SCOPE & Vellore Institute of Technology, Student

²SCOPE & Vellore Institute of Technology, Professor

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Abstract - The study of text analysis is a relatively new discipline. The technique of evaluating and extracting information from textual data is already being used in a variety of fields, including marketing, product management, academics, and governance. The act of selecting acceptable categories from a predefined set and applying them to natural language texts is known as text classification or text categorization. Text classification, to put it simply, is the process of obtaining general tags from unstructured textual content. The generation of all generic tags is done using a list of pre-defined groupings. Users will find it easier to find and navigate your website or application if you categorize your information and items.

We'll be working on a text classification model in this article that examines the textual description of a query and generates numerous labels for it. Multi-Label Text Classification, a subset of multiple output models, will be used to construct a multilabel text classification strategy for a tag recommendation system.

Key Words:  text classification, categorization, natural language processing, textual data, generic tags.