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Authors: Katashi Nagao ; Kei Inoue ; Naoya Morita and Shigeki Matsubara

Affiliation: Graduate School of Information Science and Nagoya University, Japan

Keyword(s): Discussion Mining, Discussion Structure, Task Statement, Automatic Extraction, Probability Model.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining Text and Semi-Structured Data ; Symbolic Systems

Abstract: We previously developed a discussion mining system that records face-to-face meetings in detail, analyzes their content, and conducts knowledge discovery. Looking back on past discussion content by browsing documents, such as minutes, is an effective means for conducting future activities. In meetings at which some research topics are regularly discussed, such as seminars in laboratories, the presenters are required to discuss future issues by checking urgent matters from the discussion records. We call statements including advice or requests proposed at previous meetings “task statements” and propose a method for automatically extracting them. With this method, based on certain semantic attributes and linguistic characteristics of statements, a probabilistic model is created using the maximum entropy method. A statement is judged whether it is a task statement according to its probability. A seminar-based experiment validated the effectiveness of the proposed extraction method.

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Paper citation in several formats:
Nagao, K.; Inoue, K.; Morita, N. and Matsubara, S. (2015). Automatic Extraction of Task Statements from Structured Meeting Content. In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - KDIR; ISBN 978-989-758-158-8; ISSN 2184-3228, SciTePress, pages 307-315. DOI: 10.5220/0005609703070315

@conference{kdir15,
author={Katashi Nagao. and Kei Inoue. and Naoya Morita. and Shigeki Matsubara.},
title={Automatic Extraction of Task Statements from Structured Meeting Content},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - KDIR},
year={2015},
pages={307-315},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005609703070315},
isbn={978-989-758-158-8},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - KDIR
TI - Automatic Extraction of Task Statements from Structured Meeting Content
SN - 978-989-758-158-8
IS - 2184-3228
AU - Nagao, K.
AU - Inoue, K.
AU - Morita, N.
AU - Matsubara, S.
PY - 2015
SP - 307
EP - 315
DO - 10.5220/0005609703070315
PB - SciTePress