KnowBots: Discovering Relevant Patterns in Chatbot Dialogues

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2019

Autores

Adriano Rivolli (Autor) Outra; Catarina Amaral (Autor) Outra; Luís Guardão (Autor) Outra; Cláudio Rebelo de Sá (Autor) Outra; Carlos Soares (Autor) FEUP

Ata de Conferência Internacional

Título: Discovery Science - 22nd International Conference, DS 2019, Split, Croatia, October 28-30, 2019, Proceedings

Páginas: 481-492

22nd International Conference on Discovery Science, DS 2019

28 October 2019 through 30 October 2019

Indexação

Scopus - 3 Citações

Outras Informações

ID Authenticus: P-00R-FEK

DOI: 10.1007/978-3-030-33778-0_36

Abstract (EN): Chatbots have been used in business contexts as a new way of communicating with customers. They use natural language to interact with the customers, whether while offering products and services, or in the support of a specific task. In this context, an important and challenging task is to assess the effectiveness of the machine-to-human interaction, according to business¿ goals. Although several analytic tools have been proposed to analyze the user interactions with chatbot systems, to the best of our knowledge they do not consider user-defined criteria, focusing on metrics of engagement and retention of the system as a whole. For this reason, we propose the KnowBots tool, which can be used to discover relevant patterns in the dialogues of chatbots, by considering specific business goals. Given the non-trivial structure of dialogues and the possibly large number of conversational records, we combined sequential pattern mining and subgroup discovery techniques to identify patterns of usage. Moreover, a friendly user-interface was developed to present the results and to allow their detailed analysis. Thus, it may serve as an alternative decision support tool for business or any entity that makes use of this type of interactions with their clients. © Springer Nature Switzerland AG 2019.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12