A study on the acquisition of users' values through interactive approach
Project/Area Number |
16H05880
|
Research Category |
Grant-in-Aid for Young Scientists (A)
|
Allocation Type | Single-year Grants |
Research Field |
Library and information science/Humanistic social informatics
|
Research Institution | The University of Electro-Communications (2019) Hiroshima City University (2016-2018) |
Principal Investigator |
Inaba Michimasa 電気通信大学, 人工知能先端研究センター, 准教授 (10636202)
|
Project Period (FY) |
2016-04-01 – 2020-03-31
|
Project Status |
Completed (Fiscal Year 2019)
|
Budget Amount *help |
¥20,930,000 (Direct Cost: ¥16,100,000、Indirect Cost: ¥4,830,000)
Fiscal Year 2019: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Fiscal Year 2018: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2017: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2016: ¥13,390,000 (Direct Cost: ¥10,300,000、Indirect Cost: ¥3,090,000)
|
Keywords | 知的対話システム / 対話処理 / 対話システム / ユーザモデリング / コーパス / 興味推定 / 対話破綻検出 / 自然言語処理 |
Outline of Final Research Achievements |
In this study, we proposed (1) a dialogue model based on a recurrent neural network, and (2) a model to estimate the user's interest in topics (e.g., music, fashion, health, etc.) based on the utterances in chat dialogues.
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Academic Significance and Societal Importance of the Research Achievements |
深層学習を用いた応答選択に基づく対話モデルは近年は非常に活発に研究が行われているが,提案モデルはその先駆けとなる研究の一つであり,学術的に一定のインパクトが有ったと考える.また,興味推定モデルに関しても,システムのパーソナライズに必要な技術であり,ユーザビリティの向上に有用な技術である.
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Report
(5 results)
Research Products
(22 results)