The crucial task of analysing the complex dynamics of the research landscape and uncovering the latest insights from the scientific literature is of paramount importance to researchers, governments, and commercial organizations. Springer Nature, one of the leading academic publishers worldwide, plays a significant role in this domain and regularly integrates and processes a variety of data sources to inform strategic decisions. Since exploring the resulting data is a challenging task, in 2021 we developed AIDA-Bot, a chatbot that addresses inquiries about the research landscape by utilising a large-scale knowledge graph of scholarly data. This paper presents the novel AIDA-Bot 2.0, which can both 1) support a set of predetermined question types by automatically translating them to formal queries on the knowledge graph, and 2) answer open questions by summarising information from relevant articles. We evaluated the performance of AIDA-Bot 2.0 through a comparative assessment against alternative architectures and an extensive user study. The results indicate that the novel features provide more accurate information and an excellent user experience.
Meloni, A., Angioni, S., Salatino, A., Osborne, F., Birukou, A., Reforgiato Recupero, D., et al. (2023). AIDA-Bot 2.0: Enhancing Conversational Agents with Knowledge Graphs for Analysing the Research Landscape. In The Semantic Web – ISWC 2023 22nd International Semantic Web Conference, Athens, Greece, November 6–10, 2023, Proceedings, Part II (pp.400-418). Springer Cham [10.1007/978-3-031-47243-5_22].
AIDA-Bot 2.0: Enhancing Conversational Agents with Knowledge Graphs for Analysing the Research Landscape
Osborne, Francesco;
2023
Abstract
The crucial task of analysing the complex dynamics of the research landscape and uncovering the latest insights from the scientific literature is of paramount importance to researchers, governments, and commercial organizations. Springer Nature, one of the leading academic publishers worldwide, plays a significant role in this domain and regularly integrates and processes a variety of data sources to inform strategic decisions. Since exploring the resulting data is a challenging task, in 2021 we developed AIDA-Bot, a chatbot that addresses inquiries about the research landscape by utilising a large-scale knowledge graph of scholarly data. This paper presents the novel AIDA-Bot 2.0, which can both 1) support a set of predetermined question types by automatically translating them to formal queries on the knowledge graph, and 2) answer open questions by summarising information from relevant articles. We evaluated the performance of AIDA-Bot 2.0 through a comparative assessment against alternative architectures and an extensive user study. The results indicate that the novel features provide more accurate information and an excellent user experience.
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