Machine Learning for Veracity of Big DataSpeaker: Vishnu S Pendyala – San Jose, CA, United States
Topic(s): Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing
Machine Learning is increasingly proving itself to be the mortar of modernization. The talk will examine how Machine Learning can be applied to the problem of veracity of Big Data, particularly, Web information. We are overwhelmingly depending on data for crucial tasks like driving as in self-driving cars, delivery as in autonomous drones and even in electing Presidents of countries, owing to the role of Online Social Networks like Twitter in these elections. Trusting technology has become inevitable. Compromising the quality of data in these circumstances can be hazardously risky. Ideally, data should be entirely truthful and accurate. However, there have been a number of instances where data was manipulated or posted fraudulently for ulterior motives, causing serious damage. Misinformation Containment is indeed a difficult task and computationally, has been proven to be NP-hard .
The Web is an important enabler of the evolving world economy and has the potential to bring more and more people into the mainstream . The Web, being humanity's largest source of information and interaction, can serve as a conduit of humanitarian services and presents a huge opportunity to enhance the quality of life further . Unfortunately, a significant percent of the information posted on the Web is not entirely true, which substantially limits its ability to serve the needs of the humanity . this talk will go deeper into the ideas from Machine Learning to see how we can help make the World Wide Web, particularly the Social Media part of it, entirely truthful, which should ideally be an important milestone to achieve in the near future. The talk will draw from the speaker's book .
 Budak, C., Agrawal, D., & El Abbadi, A. (2011, March). Limiting the
spread of misinformation in social networks. In Proceedings of the 20th
international conference on World wide web (pp. 665-674). ACM.
 Pendyala, Vishnu S., and Simon SY Shim. "The Web as the ubiquitous computer." IEEE Computer 42.9 (2009): 90-92.
 Pendyala, Vishnu S., Simon SY Shim, and Christoph Bussler. "The web that extends beyond the world." Computer 48.5 (2015): 18-25.
 Pendyala, Vishnu S., and Silvia Figueira. "Towards a truthful world wide web from a humanitarian perspective." Global Humanitarian Technology Conference (GHTC), 2015 IEEE. IEEE, 2015.
 Pendyala, Vishnu S. Veracity of Big Data: Machine Learning and Other
Approaches to Verifying Truthfulness. Springer, 2018.
About this LectureNumber of Slides: 30
Duration: 45 - 60 minutes
Languages Available: English, Hindi
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