Conquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphs
| Main Author: | |
|---|---|
| Publication Date: | 2020 |
| Format: | Master thesis |
| Language: | por |
| Source: | Repositório Institucional da Universidade Federal do Ceará (UFC) |
| Download full: | http://www.repositorio.ufc.br/handle/riufc/51040 |
Summary: | In this dissertation CONQUEST is presented, a framework that automates much of the construction process of chatbots for the task of Template-based Interactive Question Answering (TBIQA) for Closed Domain Knowledge Graphs (KG). The chatbots produced by CONQUEST are able to answer questions issued in natural language, using conversation to solve the possible problems of ambiguity and the lack of information needed to formulate the answer. For the interpretation of the question, the system performs the process of classifying the user intention to one of the templates defined by the developer a priori. For this, CONQUEST has a flexible question classification mechanism based on Machine learning (ML) that uses both textual features and semantic features and that adapts to use, learning new ways how the same question can be realized. This classification mechanism makes a chatbot capable of dealing with the problem of linguistic variability. In addition, a chatbot produced by CONQUEST uses the user feedback in its training, adapting to the use. As main contributions of this work, we have: (1) A new architecture for chatbots for gls TBIQA and (2) A tool for the automatic building of chatbots for TBIQA for KGs. Finally, with CONQUEST, the developer invests his time only in creating the question templates supported by the system, leaving the control of messages, natural language processing, question interpretation, querying data sources and generating responses for the framework deal with it. |
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Avila, Caio Viktor da SilvaVidal, Vânia Maria Ponte2020-03-31T18:51:23Z2020-03-31T18:51:23Z2020AVILA, Caio Viktor da Silva. Conquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphs. 2020. 113 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal do Ceará, Fortaleza, 2020.http://www.repositorio.ufc.br/handle/riufc/51040In this dissertation CONQUEST is presented, a framework that automates much of the construction process of chatbots for the task of Template-based Interactive Question Answering (TBIQA) for Closed Domain Knowledge Graphs (KG). The chatbots produced by CONQUEST are able to answer questions issued in natural language, using conversation to solve the possible problems of ambiguity and the lack of information needed to formulate the answer. For the interpretation of the question, the system performs the process of classifying the user intention to one of the templates defined by the developer a priori. For this, CONQUEST has a flexible question classification mechanism based on Machine learning (ML) that uses both textual features and semantic features and that adapts to use, learning new ways how the same question can be realized. This classification mechanism makes a chatbot capable of dealing with the problem of linguistic variability. In addition, a chatbot produced by CONQUEST uses the user feedback in its training, adapting to the use. As main contributions of this work, we have: (1) A new architecture for chatbots for gls TBIQA and (2) A tool for the automatic building of chatbots for TBIQA for KGs. Finally, with CONQUEST, the developer invests his time only in creating the question templates supported by the system, leaving the control of messages, natural language processing, question interpretation, querying data sources and generating responses for the framework deal with it.Nesta dissertação é apresentado CONQUEST, um framework que automatiza grande parte do processo de construção de chatbots para a tarefa de Template-based Interactive Question Answering (TBIQA) sobre Knowledge Graphs (KG) de Domínio Fechado. Os chatbots produzidos por CONQUEST são capazes de responder questões emitidas em linguagem natural, utilizando a conversação para solucionar os possíveis problemas da ambiguidade e da falta de informação necessária para a formulação da resposta. Para a interpretação da questão, o sistema realiza o processo de classificação de sua intenção para um dos padrões definidos pelo desenvolvedor à priore. Para isto, CONQUEST conta com um mecanismo flexível de classificação de questões baseado em aprendizado de máquina (Machine learning, ML) que utiliza tanto features textuais, quanto features semânticas e que se adapta ao uso, aprendendo novas maneiras como uma mesma questão pode ser realizada. Este mecanismo de classificação torna um chatbot capaz de tratar o problema da variabilidade linguística. Além disso, um chatbot produzido por CONQUEST utiliza o feedback do usuário no seu treinamento, adaptando-se ao uso. Como principais contribuições deste trabalho, temos: (1) Uma nova arquitetura para chatbots de Template-Based Interactive Question Answering (TBIQA) e (2) Uma ferramenta para a criação automática de chatbots de TBIQA para Knowledge Graph (KG)s. Por fim, com CONQUEST, o desenvolvedor investe seu tempo apenas na criação dos padrões de questões suportados pelo sistema, deixando o controle de mensagens, processamento de linguagem natural, interpretação da questão, consulta às fontes de dados e geração das respostas para o framework.Interactive question answeringChatBotKnowledge graphLinked dataFrameworkConquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphsConquest: a framework for building template-based IQA chatbots for knowledge graphinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisporreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccessORIGINAL2020_dis_cvsavila.pdf2020_dis_cvsavila.pdfapplication/pdf2913886http://repositorio.ufc.br/bitstream/riufc/51040/3/2020_dis_cvsavila.pdfb32b0d178e1fe6379d7c976cc2eecfa1MD53LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.ufc.br/bitstream/riufc/51040/4/license.txt8a4605be74aa9ea9d79846c1fba20a33MD54riufc/510402020-03-31 15:51:23.512oai:repositorio.ufc.br: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Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2020-03-31T18:51:23Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false |
| dc.title.pt_BR.fl_str_mv |
Conquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphs |
| dc.title.en.pt_BR.fl_str_mv |
Conquest: a framework for building template-based IQA chatbots for knowledge graph |
| title |
Conquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphs |
| spellingShingle |
Conquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphs Avila, Caio Viktor da Silva Interactive question answering ChatBot Knowledge graph Linked data Framework |
| title_short |
Conquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphs |
| title_full |
Conquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphs |
| title_fullStr |
Conquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphs |
| title_full_unstemmed |
Conquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphs |
| title_sort |
Conquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphs |
| author |
Avila, Caio Viktor da Silva |
| author_facet |
Avila, Caio Viktor da Silva |
| author_role |
author |
| dc.contributor.author.fl_str_mv |
Avila, Caio Viktor da Silva |
| dc.contributor.advisor1.fl_str_mv |
Vidal, Vânia Maria Ponte |
| contributor_str_mv |
Vidal, Vânia Maria Ponte |
| dc.subject.por.fl_str_mv |
Interactive question answering ChatBot Knowledge graph Linked data Framework |
| topic |
Interactive question answering ChatBot Knowledge graph Linked data Framework |
| description |
In this dissertation CONQUEST is presented, a framework that automates much of the construction process of chatbots for the task of Template-based Interactive Question Answering (TBIQA) for Closed Domain Knowledge Graphs (KG). The chatbots produced by CONQUEST are able to answer questions issued in natural language, using conversation to solve the possible problems of ambiguity and the lack of information needed to formulate the answer. For the interpretation of the question, the system performs the process of classifying the user intention to one of the templates defined by the developer a priori. For this, CONQUEST has a flexible question classification mechanism based on Machine learning (ML) that uses both textual features and semantic features and that adapts to use, learning new ways how the same question can be realized. This classification mechanism makes a chatbot capable of dealing with the problem of linguistic variability. In addition, a chatbot produced by CONQUEST uses the user feedback in its training, adapting to the use. As main contributions of this work, we have: (1) A new architecture for chatbots for gls TBIQA and (2) A tool for the automatic building of chatbots for TBIQA for KGs. Finally, with CONQUEST, the developer invests his time only in creating the question templates supported by the system, leaving the control of messages, natural language processing, question interpretation, querying data sources and generating responses for the framework deal with it. |
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2020 |
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2020-03-31T18:51:23Z |
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2020-03-31T18:51:23Z |
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2020 |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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AVILA, Caio Viktor da Silva. Conquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphs. 2020. 113 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal do Ceará, Fortaleza, 2020. |
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http://www.repositorio.ufc.br/handle/riufc/51040 |
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AVILA, Caio Viktor da Silva. Conquest: um framework para a construção de chatbots de IQA baseados em templates sobre knowledges graphs. 2020. 113 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal do Ceará, Fortaleza, 2020. |
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