The Fifth Elephant 2017

On data engineering and application of ML in diverse domains


How to read a user's mind? Designing algorithms for contextual recommendations

Submitted by Bharath Mohan (@bharathmohan) on Monday, 22 May 2017

Section: Crisp talk for data engineering track Technical level: Beginner


The human mind is going through thousands of thoughts everyday. A perfect recommender system needs to know what is going on and suggest something useful - at all times, without being perceived as intrusive or noisy. After slicing every possible sensor within the reach of a digital system - from the GPS, Accelerometer, Time of day, Temperature, Browsing History, TV Viewing, Sound, a “perfect recommender system” should learn which ones to give more importance to, predict the state of mind - in order to make the most effective recommendations. This talk takes an exemplary approach to derive some heuristics that can drive these algorithms.


Speaker bio

Bharath Mohan is CEO of Sensara, a company that provides Smarter Live TV User Experience & Monetization. Sensara offers Smart Remotes, TV Search & Personalization, Smart TV Interfaces and TV Deep Data Mining. Bharath earlier worked for Google, and was part of the launch team in Google Finance, and also a technical lead for Google News. Bharath has a PhD in Computer Science from the Indian Institute of Science.



  • Abhishek Balaji (@booleanbalaji) Reviewer 2 years ago

    Hi Bharath,

    Please upload a two-min preview video explaining what the talk is about and what is the key takeaway for participants. We need this information by 29 May to evaluate your proposal.

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