Developing a Method for Quantifying Degree of Discussion Progress Towards Automatic Facilitation of Web-Based Discussion

Kitagawa, Ko; Shiramatsu, Shun; Kamiya, Akira

doi:10.1007/978-3-030-17294-7_12

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…From this viewpoint, the explainability can be ensured by generating questions and multiple hypotheses for each question and by evaluating each hypothesis. This idea is inspired by a research project [5,6] to develop autonomous facilitator agents for online discussion based on generating facilitators' questions using the issue-based information system (IBIS) [7].…”

Section: Submission Of Nagoya Institute Of Technologymentioning

confidence: 99%

“…Over more than a week, the experts evaluated the following aspects according to five grades (1)(2)(3)(4)(5). For estimation and/or reasoning methods, they considered: Significance: Novelty and technical improvement of the method.…”

Section: Expert Evaluationmentioning

confidence: 99%

“…In the presentation before the examination, the applicants had 15 min to present their submissions (10 min for idea-only submissions). In November 2018, the 45 participants of the SIGSWO meeting answered to the total score and explainability according to five grades (1)(2)(3)(4)(5). The forms were distributed in advance, and explained.…”

Section: General Examinationmentioning

confidence: 99%

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Report on the First Knowledge Graph Reasoning Challenge 2018

Kawamura

Egami

Tamura

et al. 2020

Semantic Technology

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A new challenge for knowledge graph reasoning started in 2018. Deep learning has promoted the application of artificial intelligence (AI) techniques to a wide variety of social problems. Accordingly, being able to explain the reason for an AI decision is becoming important to ensure the secure and safe use of AI techniques. Thus, we, the Special Interest Group on Semantic Web and Ontology of the Japanese Society for AI, organized a challenge calling for techniques that reason and/or estimate which characters are criminals while providing a reasonable explanation based on an open knowledge graph of a well-known Sherlock Holmes mystery story. This paper presents a summary report of the first challenge held in 2018, including the knowledge graph construction, the techniques proposed for reasoning and/or estimation, the evaluation metrics, and the results. The first prize went to an approach that formalized the problem as a constraint satisfaction problem and solved it using a lightweight formal method; the second prize went to an approach that used SPARQL and rules; the best resource prize went to a submission that constructed word embedding of characters from all sentences of Sherlock Holmes novels; and the best idea prize went to a discussion multi-agents model. We conclude this paper with the plans and issues for the next challenge in 2019.

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Section: Submission Of Nagoya Institute Of Technologymentioning

confidence: 99%