11 citations · 14 across the 6 of their papers we have counts for
6 papers · 1 filter
Using Meta-Knowledge Mined from Identifiers to Improve Intent Recognition in Neuro-Symbolic Algorithms
Claudio Pinhanez, Paulo Cavalin, Victor Ribeiro +8
In this paper we explore the use of meta-knowledge embedded in intent identifiers to improve intent recognition in conversational systems. As evidenced by the analysis of thousands…
A Hybrid Solution to Learn Turn-Taking in Multi-Party Service-based Chat Groups
Maira Gatti de Bayser, Melina Alberio Guerra, Paulo Cavalin +1
To predict the next most likely participant to interact in a multi-party conversation is a difficult problem. In a text-based chat group, the only information available is the send…
Learning Multi-Party Turn-Taking Models from Dialogue Logs
Maira Gatti de Bayser, Paulo Cavalin, Claudio Pinhanez +1
This paper investigates the application of machine learning (ML) techniques to enable intelligent systems to learn multi-party turn-taking models from dialogue logs. The specific M…
Combining Textual Content and Structure to Improve Dialog Similarity
Ana Paula Appel, Paulo Rodrigo Cavalin, Marisa Affonso Vasconcelos +1
Chatbots, taking advantage of the success of the messaging apps and recent advances in Artificial Intelligence, have become very popular, from helping business to improve customer…
Methodology and Results for the Competition on Semantic Similarity Evaluation and Entailment Recognition for PROPOR 2016
Luciano Barbosa, Paulo R. Cavalin, Victor Guimaraes +1
In this paper, we present the methodology and the results obtained by our teams, dubbed Blue Man Group, in the ASSIN (from the Portuguese {\it Avaliação de Similaridade Semântica e…
A Hybrid Architecture for Multi-Party Conversational Systems
Maira Gatti de Bayser, Paulo Cavalin, Renan Souza +4
Multi-party Conversational Systems are systems with natural language interaction between one or more people or systems. From the moment that an utterance is sent to a group, to the…