Closed meghanabhange closed 5 years ago
Woohoo @meghanabhange 💯 🎉
@meghanabhange Are you available to present it this Saturday?
Yes. I'll be available.
Awesome, see you on Saturday! I've updated the agenda on the Meetup event. You have the first talk at 10:30am.
@meghanabhange Can you post the slides here?
@vinayak-mehta Yepp. Here are the talk slides :)
https://docs.google.com/presentation/d/1J6655pke8YM_fuXjLmWABGLcuWh5kWD6u6v9FD22si8/edit?usp=sharing
Thanks!
Extracting Names from multi-lingual conversation
Description
Chatbots are an upcoming and automated way employed by businesses to communicate with their clients. An important aspect of personalising this communication is to employ natural language rather than use text boxes with strict bounds. As part of this, it is important to extract named entities(to understand the customer’s name) from messages written in unstructured, natural language. This problem is called Named Entity Recognition.
Named Entity Recognition for Chats can face several issues like inputs consisting of-
This talk would focus on creating an efficient NER for chats by tweaking the current state of the art NER’s
Duration
Audience
Prerequisites: This is a beginner friendly talk. Prior knowledge of NLP jargon is not expected.
Outline
Introduction [5 mins]
Current state-of-the-art work [5 mins]
Dealing with chat (human conversation) specific cases [10 mins]
Taking context into consideration [5 mins]
Wrap up and questions [5 mins]
[ ] Don't record this talk.