SucupiraBot - An Interactive Question-Answering System for the Sucupira Platform

• Ivan Pereira PUC-Rio
• Jéssica Sousa PUC-Rio
• Polyana B. Costa PUC-Rio
• Simone D. J. Barbosa PUC-Rio
• Sérgio Colcher PUC-Rio

Resumo

Conversational user interfaces have been an increasingly popular way to obtain quick information in natural language, especially with advances in the area of natural language processing (NLP) fueled by the surge of deep neural networks. Real-world cases include IBM Watson and Azure Microsoft chatbots, among others. Such examples, however, are most present in the commercial spectrum, with few being actively used by the scientific community. In this work, we develop an Interactive Question Answering System (IQA) for the Sucupira platform, Brazil's biggest open platform of postgraduate content, deployed as conversational interfaces for two popular messaging platforms: Telegram and Discord. We also propose the use of multilingual embeddings for ordering answers by a language-independent measuer of semantic similarity. Our IQA was evaluated with an study with 16 participants. The results were mostly positive, indicating that the use of conversational user interfaces, along with NLP techniques, may be a valid alternative for retrieving scientific information from the Sucupira plataform.

Palavras-chave: Interactive Question Answering, Chatbots, Embeddings, Natural language Processing, Open Data