by Anuj Gupta (@anuj-gupta) on Tuesday, 8 May 2018

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Status: Confirmed & Scheduled
Section
Full talk

Technical level
Intermediate

Abstract

Sentiment analysis has been for long poster boy problem of NLP and has attracted a lot of research. However, despite so much work in this sub area, most sentiment analysis models fail miserably in handling sarcasm. Rise in usage of sentiment models for analysis social data has only exposed this gap further. Owing to the subtilty of language involved, sarcasm detection is a hard problem.

Most attempts at sarcasm detection still depend on hand crafted features which are dataset specific. In this talk we see some of the very recent attempts to leverage recent advances in NLP for building generic models for sarcasm detection.

Key take aways:
+ Challenges in sarcasm detection
+ Deep dive into a end to end solution using DL to build generic models for sarcasm detection
+ Short comings and road forward

Outline

Key take aways:
+ Challenges in sarcasm detection
+ Deep dive into a end to end solution using DL to build generic models for sarcasm detection
+ Short comings and road forward

Speaker bio

Anuj is currently working as Director - Machine Learning at Huawei. He has headed ML efforts at a bunch of organizations. Prior to that, he dropped out of Phd to work with startups, completed his master’s with a specialization in theoretical computer science.

Speaker at various forums like Anthill, Nvidia forums, PyData, Fifth Elephant, ICDCN, PODC.
More about him - https://www.linkedin.com/in/anuj-gupta-15585792/