Machine Learning in Automated Text Categorization

Title: Machine Learning in Automated Text Categorization

Research Question: How can machine learning techniques be used to categorize texts into predefined categories?

Methodology: The study discusses three main problems in text categorization: document representation, classifier construction, and classifier evaluation. It explores various machine learning approaches to solve these problems and compares their effectiveness.

Results: The research found that machine learning techniques can automatically build a classifier by learning from a set of preclassified documents. This approach has proven to be effective, efficient, and portable to different domains.

Implications: The study suggests that machine learning is a promising approach for automated text categorization. It can save time and resources by eliminating the need for manual rule creation and expert intervention. Moreover, it allows for adaptability to different domains, making it a versatile tool for information retrieval and management.

Link to Article: https://arxiv.org/abs/0110053v1 Authors: arXiv ID: 0110053v1