NEW YORK â Using machine learning, a team of U.S. researchers led by Indian American computer scientist Anshumali Shrivastava at Rice University has discovered an efficient way for social media companies to keep misinformation from spreading online.
Their method applies machine learning in a smarter way to improve the performance of Bloom filters, a widely used technique devised a half-century ago.
Using test databases of fake news stories and computer viruses, Shrivastava and statistics graduate student Zhenwei Dai showed their Adaptive Learned Bloom Filter required 50 percent less memory to achieve the same level of performance as learned Bloom filters.
To explain their filtering approach, Shrivastava and Dai cited some data from Twitter.
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New York: Using machine learning (ML), a team of US researchers led by Indian-American computer scientist Anshumali Shrivastava at Rice University has discovered an efficient way for social media companies to keep misinformation from spreading online.
Their method applies machine learning in a smarter way to improve the performance of Bloom filters, a widely used technique devised a half-century ago.
Using test databases of fake news stories and computer viruses, Shrivastava and statistics graduate student Zhenwei Dai showed their Adaptive Learned Bloom Filter (Ada-BF) required 50 per cent less memory to achieve the same level of performance as learned Bloom filters.
14 December 2020, 12:59 am EST By
With so much misinformation spreading in social media, Rice University researchers led by computer scientist Anshumali Shrivastava developed a method using machine learning (ML) to prevent the spread of misinformation online.
This new method developed by Shrivastava and his team is presented during the 2020 Conference on Neural Information Processing Systems (NeurIPS 2020), which was held online. They improved the 50-year old Bloom filter technology for scanning social media help social media network companies prevent the spread of fake news in their platforms.
What are bloom filters?
A Bloom filter is a data structure used to test whether a certain element is a member of a set. It is
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