DisBot: A Portuguese Disaster Support Dynamic Knowledge Chatbot

Abstract

This paper presents DisBot, the first Portuguese speaking chatbot that uses social media retrieved knowledge to support citizens and first-responders in disaster scenarios, in order to improve community resilience and decision-making. It was developed and tested using Design Science Research Methodology (DSRM), being progressively matured with field specialists through several design and development iterations. DisBot uses a state-of-the-art Dual Intent Entity Transformer (DIET) architecture to classify user intents, and makes use of several dialogue policies for managing user conversations, as well as storing relevant information to be used in further dialogue turns. To generate responses, it uses real-world safety knowledge, and infers a dynamic knowledge graph that is dynamically updated in real-time by a disaster-related knowledge extraction tool, presented in previous works. Through its development iterations, DisBot has been validated by field specialists, who have considered it to be a valuable asset in disaster management. View Full-Text

Publication regarding the second artifact (work held in Chapter 4 and the artifact’s validation of Chapter 5) of the MSc thesis in MIBIS, from Boné J.

 

Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL

DisKnow: A Social-Driven Disaster Support Knowledge Extraction System

Abstract

This research is aimed at creating and presenting DisKnow, a data extraction system with the capability of filtering and abstracting tweets, to improve community resilience and decision-making in disaster scenarios. Nowadays most people act as human sensors, exposing detailed information regarding occurring disasters, in social media. Through a pipeline of natural language processing (NLP) tools for text processing, convolutional neural networks (CNNs) for classifying and extracting disasters, and knowledge graphs (KG) for presenting connected insights, it is possible to generate real-time visual information about such disasters and affected stakeholders, to better the crisis management process, by disseminating such information to both relevant authorities and population alike. DisKnow has proved to be on par with the state-of-the-art Disaster Extraction systems, and it contributes with a way to easily manage and present such happenings. View Full-Text

Publication regarding the first artifact (work held in Chapter 3) of the MSc thesis in MIBIS, from Boné J.

 

Master in Integrated Business Intelligence Systems (MIBIS) - ISCTE-IUL