In this topic, the student will implement and deploy a live chatbot version of the DBpedia Neural Question Answering dataset .
Create a life DBpedia Neural Chatbot based on DBNQA and NSpM.
(1) Facilitate access to DBpedia content;
(2) Enable community evaluation and feedback of DBpedia NSpM models.
(1) Fork the NsPM project (https://github.com/AKSW/NSPM );
(2) Train the Monument 300 and Monument 600 datasets https://github.com/AKSW/NSpM/tree/master/data;
(4) Fork and train the model using a subset (30 first lines) of DBNQA dataset https://github.com/AKSW/dbnqa;
(5) Instantiate the NSpM Telegram Chatbot: https://github.com/AKSW/NSpM/wiki/NSpM-Telegram-Bot
“An example of an excellent proposal that was accepted a few years ago. Please mind that the number of total project hours have changed from 300 to 175.” Tommaso Soru
Google Dialog Flow
Because, why not? Tutorial: https://cloud.google.com/dialogflow/es/docs/tutorials?hl=en
The DBpediaChatBot (http://chat.dbpedia.org/)
It will be interesting to re-use their interface
Thiago Castro Ferreira
#NSpM #DBpedia #Chatbot #AI #ConversationalAI