MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641049984 A) filed by Sree Chaitanya College Of Engineering, Karimnagar, Telangana, on April 20, for 'using machine learning classifier to evaluate the reliability of web information contents.'
Inventor(s) include Mr. Arun Kumar Savalla; Mr. Thumma Muthaiah; Mr. Gagan Guptha; Ms. Nampally Lalitha.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "Social networking, information sharing, knowledge imparting, discussions on current happenings etc. are always apart of human society. With the fast pace of life and advancement in technology; people rely more on online information, as a result of this web platforms have become a dominant place for social into reactions. This has given rise to unverified and unauthenticated news that has extremely negative effects. Fake news, rumor, mis information, dis information, satire, hoax, clickbait, propaganda are all different flavors of these emalice of information pollution. Their search community is constantly trying to figure out a viable technical solution to this problem indifferent ways. In this work, we designed a framework based on five independent supervised machine-learned classifiers Support Vector Machine, K-Nearest Neighbor, Logistic Regression, Naive Bayes and Random Forest for trustworthiness assessment of web information contents. The classifiers are being trained and tested on two different datasets: Fake News Detection (Jruvika /FND) and Real or Fake News that contains full news articles in the form of headline and body. Experiments and result analysis verify that the highest accuracy attained by the projected method is 96.61% on the Fake News Detection dataset using the SVM classifier. The work is also compared with other contemporary techniques."
Disclaimer: Curated by HT Syndication.
