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A vertical Retrieval based AI conversational agent
Design and deployment of a retrieval based AI chatbot ready to be deployed as a product. ...learn more
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Student Developers for AI
Overview / Usage
We are designing an AI solution for scheduling meetings. It will be a chatbot that will help its users schedule, reschedule and update meetings with their guests/clients by automating the task.
Currently, we are classifying the intent of an utterance using seq2seq and other RNN-based models. The bottleneck we are facing is in named entity recognition and ranking. We are on the hunt for someone who has experience in building chatbots. Our workflow pipeline will be:
1. Intent Classification: Given a mail, classify it based on the sender's intention. E.g., Schedule, Cancel, Reschedule, Update Preference, etc.
2. Entity Extraction: Given a mail, tag each word to a concept E.g., New York -> location, today-> time
3. Response Repository: Templates for various responses
4. Response Ranking: Given potential responses, try to find the best response
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