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Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Subhabaha Pal, T. K. Senthil Kumar | - |
dc.date.accessioned | 2023-09-11T10:28:59Z | - |
dc.date.available | 2023-09-11T10:28:59Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/1053 | - |
dc.description.abstract | Spread of fake news has become a big problem in recent times and this has become a source of discomfort in the society in many instances. Application of sophisticated Machine Learning algorithms for detection of fake news has shown some success and it is a new area which shows immense opportunities for practical use and further research. The detection of fake news using machine learning algorithms have been discussed in details in this paper. News items are unstructured data and this paper shows how unstructured news items can be turned into structured form using Count vectorization and TFIDF vectorization techniques. This paper also shows how machine learning models can be developed and the classification can be done using the newly structured data employing sophisticated developed Machine Learning algorithms. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Indian Journal of Computer Science | en_US |
dc.subject | Count Vectorizer | en_US |
dc.subject | Machine Learning | en_US |
dc.subject | Fake news detection | en_US |
dc.subject | NLP | en_US |
dc.subject | TFIDF Vectorizer | en_US |
dc.subject | Text Analytics | en_US |
dc.title | Applying Machine Learning to Detect Fake News | en_US |
dc.type | Article | en_US |
Appears in Collections: | Article Archives |
Files in This Item:
File | Description | Size | Format | |
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Applying Machine Learning to Detect Fake News.pdf Restricted Access | Applying Machine Learning to Detect Fake News | 386.99 kB | Adobe PDF | View/Open Request a copy |
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