Isbn: 9786630040586 - enhancing news authenticity prediction with machine learning approach (9 résultats)

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

Etat : New.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Etat : new. Paperback. The rapid proliferation of misinformation across digital platforms poses a critical threat to public discourse, democratic processes, and societal trust. Manual verification systems cannot keep pace with the volume and velocity of fake news being generated, necessitating the development of automated detection mechanisms. This work presents a lightweight machine learning approach for fake news detection using a PassiveAggressive Classifier combined with TF-IDF vectorization, trained and evaluated on the WELFake benchmark dataset comprising 72,119 news articles sourced from multiple platforms spanning 2016 to 2020. The proposed system achieves 96.19% classification accuracy on 14,424 test articles, with precision and recall scores of 0.96-0.97 for both classes and a balanced F1-score of 0.96, validated using a CalibratedClassifierCV wrapper providing calibrated probability outputs. Beyond classification, the system incorporates LIME-based explainability for word-level prediction reasoning, real-time URL verification with source credibility analysis, clickbait detection, and evidence-backed verdict generation using the Gemini API. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 56 pp. Englisch.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The rapid proliferation of misinformation across digital platforms poses a critical threat to public discourse, democratic processes, and societal trust. Manual verification systems cannot keep pace with the volume and velocity of fake news being generated, necessitating the development of automated detection mechanisms. This work presents a lightweight machine learning approach for fake news detection using a PassiveAggressive Classifier combined with TF-IDF vectorization, trained and evaluated on the WELFake benchmark dataset comprising 72,119 news articles sourced from multiple platforms spanning 2016 to 2020. The proposed system achieves 96.19% classification accuracy on 14,424 test articles, with precision and recall scores of 0.96-0.97 for both classes and a balanced F1-score of 0.96, validated using a CalibratedClassifierCV wrapper providing calibrated probability outputs. Beyond classification, the system incorporates LIME-based explainability for word-level prediction reasoning, real-time URL verification with source credibility analysis, clickbait detection, and evidence-backed verdict generation using the Gemini API.…

Paperback. Etat : new. Paperback. The rapid proliferation of misinformation across digital platforms poses a critical threat to public discourse, democratic processes, and societal trust. Manual verification systems cannot keep pace with the volume and velocity of fake news being generated, necessitating the development of automated detection mechanisms. This work presents a lightweight machine learning approach for fake news detection using a PassiveAggressive Classifier combined with TF-IDF vectorization, trained and evaluated on the WELFake benchmark dataset comprising 72,119 news articles sourced from multiple platforms spanning 2016 to 2020. The proposed system achieves 96.19% classification accuracy on 14,424 test articles, with precision and recall scores of 0.96-0.97 for both classes and a balanced F1-score of 0.96, validated using a CalibratedClassifierCV wrapper providing calibrated probability outputs. Beyond classification, the system incorporates LIME-based explainability for word-level prediction reasoning, real-time URL verification with source credibility analysis, clickbait detection, and evidence-backed verdict generation using the Gemini API. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware 56 pp. Englisch.

Taschenbuch. Etat : Neu. Enhancing News Authenticity Prediction with Machine Learning Approach | Smart News Verification | M. M. Mohod (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630040586 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.…