Abstract
Author detection is a challenging problem for articles on the Internet (forums, blogs, etc.) due to lack of substantial content. Therefore, author detection for these articles is much more difficult than books, reports and other documents. In this study, the authors of newspaper articles are categorized. We tried to detect authors of articles of test data by using frequently used words in these categories. In doing so, we applied the improved Naïve Bayesian machine learning algorithm.
Keywords
Computer science
Bayesian probability
Newspaper
The Internet
Test (biology)
Artificial intelligence
Machine learning
Algorithm
Information retrieval
World Wide Web
Advertising
Subject Areas
Authorship Attribution and Profiling
·Artificial Intelligence ·Physical Sciences
Spam and Phishing Detection
·Information Systems ·Physical Sciences
Text and Document Classification Technologies
·Artificial Intelligence ·Physical Sciences
OpenAlex SDG Match
SDGs auto-classified by OpenAlex (score ≥ 0.4 shown).
Quality Education 70%
Loading…