Extracting User Knowledge Graphs from a Large Knowledge Graph Using User's Utterance and SPARQL Templates for a Chatbot
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- SUZUKI Naho
- Aoyama Gakuin University
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- YATSU Motoki
- Aoyama Gakuin University
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- MORITA Takeshi
- Aoyama Gakuin University
Bibliographic Information
- Other Title
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- 雑談対話システムのためのユーザ発話とSPARQLテンプレートを用いた大規模知識グラフからのユーザ知識グラフ抽出
Abstract
<p>In recent years, research and development of dialogue systems have been actively carried out, and it is becoming a society in which humans and dialogue systems coexist. In order to conduct various dialogues in consideration of the user preferences in the chatbot, it is necessary to infer the knowledge possessed by the user from the user's utterance and to provide questions and topics based on the knowledge. In this research, we propose a dialogue system that allows users to chat based on the fact that some of the knowledge that the user is presumed to have from the user's utterance is extracted and accumulated from DBpedia using the SPARQL template as a user knowledge graph. It is considered that various dialogues considering the user's taste can be realized by the chat dialogue system presenting the topic based on the user knowledge graph.</p>
Journal
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- JSAI Technical Report, Type 2 SIG
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JSAI Technical Report, Type 2 SIG 2022 (SWO-056), 03-, 2022-03-11
The Japanese Society for Artificial Intelligence
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Details 詳細情報について
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- CRID
- 1390010292736272256
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- ISSN
- 24365556
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- Text Lang
- ja
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- Data Source
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- JaLC
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- Abstract License Flag
- Allowed