The Fifth Elephant 2016

India's most renowned data science conference

Meet the needs of content marketing with the power of NLP

Submitted by Balaji Vasan (@balajivasan) on Wednesday, 13 July 2016

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Technical level

Intermediate

Section

Full talk

Status

Confirmed & Scheduled

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Abstract

Content Marketing is one of the recent buzz in the space of digital marketing. Content Marketing broadly refers to focusing on providing quality and useful content to customers for engaging and attracting customers towards a brand. With the proliferation of channels where these content can potentially be delivered, there is an increasing demand from content writers to provide content that can be adapted to the needs of each of these channels. Further, the speed at which the content needs to be generated poses a unique challenge and calls for ways to aid in creating and adapting these content quickly for different channels. In this talk, I will walk through some of the recent advances in Natural Language Processing to aid in effective content authoring to meet the needs of a content writer.

Outline

I will start the talk by walking through what is Content Marketing and its needs. I will layout the different stages of content marketing. I will also outline some key challenges in Content Marketing. I will then talk about a few techniques that can aid in Content Optimization. Here I will cover out-of-the-box techniques that can be explored for quick content optimization such as summarizing a text as well as some advanced work in the direction extending the topics around a content. I will also talk about some recent works in the space of automatic content personalization for specific demographies.

Speaker bio

Balaji Vasan Srinivasan is a Computer Scientist at the Adobe Research Big data Experience Labs, Bangalore, India. His research interests span the areas of data mining, natural language processing, machine learning, social data analytics and high performance computing. He finished his Ph.D. in Computer Science at the University of Maryland in September 2011, his thesis was on Scalable Learning Methods for Speaker Recognition and Geostatistics. Prior to that, he completed his M.S. in Electrical Engineering from University of Maryland in 2008 and B.E. in Electrical Engineering from Anna University (India) in 2006. His research experience also includes stints at National Institutes of Health, Bethesda, MD (May – Aug 2007) and Xerox Research Center, Webster, NY (May – Aug 2011).

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