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<h1 class="section-header">Publications</h1>
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data-aos-once="true">
<p>Okoshi, Tadashi, et al. “Cyberoception: Finding A Painlessly-Measurable New Sense In The Cyberworld
Towards Emotion-awareness In Computing” Proceedings of the 2025 CHI Conference on Human Factors in
Computing Systems, 2025, p. 719, https://doi.org/10.1145/3706598.3713638.</p>
<p>Sasaki, Wataru, et al. “Large-Scale Estimation and Analysis of Web Users' Mood from Web Search Query
and Mobile Sensor Data” Big Data, 2024, p. 191-209, https://doi.org/10.1089/big.2022.0211.</p>
<p>Hamanaka, Satoki, et al. “Estimation of User Personality Traits on the Web Using Multi-Task
Learning.” Proceedings of the 24th International Workshop on Mobile Computing Systems and
Applications, 2023, p. 133, https://doi.org/10.1145/3572864.3581580.</p>
<p>羽柴彩月, et al. “ユーザビリティの低下による不快感を用いた SNS 利用に対するセルフコントロール手法.”
情報処理学会論文誌, vol. 64, Apr. 2023, pp. 799–813, https://doi.org/10.20729/00225487.</p>
<p>Sasaki, Wataru, et al. “Large - Scale Estimation and Analysis of Web Users’ Mood from Web Search
Query and Mobile Sensor Data.” Big Data, vol. 0, 2023, p. null,
https://doi.org/10.1089/big.2022.0211.</p>
<p>Katsumata, Kento, et al. “COVIDGuardian: A Machine Learning Approach for Detecting the Three Cs.”
Proceedings of the 12th International Conference on the Internet of Things, 2023, pp. 147–50,
https://doi.org/10.1145/3567445.3569166.</p>
<p>佐々木航, et al. “SFC GO：学生同士の繋がりを支援するオンライン体育授業サポートシステム.”
情報処理学会論文誌デジタルプラクティス（TDP）, vol. 3, no. 1, Jan. 2022, pp. 19–33.</p>
<p>Hamanaka, Satoki, et al. A Comparative Study of CIPN Symptom Estimation Methods Based on Machine
Learning. 2021, p. 4.</p>
<p>Okoshi, Tadashi, et al. “WellComp 2021: Fourth International Workshop on Computing for Well-Being.”
Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous
Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers, ACM, 2021,
pp. 108–11, https://doi.org/10.1145/3460418.3479262.</p>
<p>Sasaki, Wataru, et al. “Investigating the Occurrence of Selfie-Based Emotional Contagion over Social
Network.” Springer, vol. 11, no. 1, 2021, p. 8, https://doi.org/10.1007/s13278-020-00712-0.</p>
<p class="text-center"><a href="https://www.jn.sfc.keio.ac.jp/publication/">すべて表示</a></p>
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<h1 class="section-header">Contact</h1>
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<a href="mailto: shift-kg@sfc.keio.ac.jp"
style="color:white; text-decoration: underline;">shift-kg@sfc.keio.ac.jp</a>
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<p data-i18n="contact_address">Keio University Shonan Fujisawa CampusΔSouth Room-213
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<p>© <span id="year"></span> Nakazawa and Okoshi Laboratory</p>
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about_section_header: 'About',
about_shift: 'SHIFT (System for Human and Intelligence towards Future Transformation) research group aims to explore and design AI systems that shape and support the future transformation of human life. By envisioning how people’s lives may evolve over the next 10 to 15 years, SHIFT seeks to develop intelligent technologies that enhance human well-being, adaptability, and societal harmony in a rapidly changing world.',
projects_header_1: 'Adaptive Push Notification for Behavioral Change in Lifelogging Services',
projects_description_1: "This study aimed to improve continuous lifelog entries for conversational health apps by testing three prompt methods: (a) personalized wording, (b) timing based on physical activity, and (c) a combination of both.",
projects_header_2: 'EmoGO',
projects_description_2: "EmoGO is a system that records the objects seen and the emotions recalled by detecting objects in the field of vision by estimating emotions based on eye tracking data. To confirm the effectiveness of the system, user experiments were conducted at Keio University's Shonan Fujisawa Campus and at Samukawa Shrine.",
projects_header_3: 'Smartphone-based activity and emotion-aware music streaming recommendation system',
projects_description_3: "smartphone-based system that recommends music based on human activities and emotional states. The system has three modules: recognizing activities, detecting emotions, and recommending music. We use machine learning to interpret smartphone signals and collaborative filtering for music recommendations.",
projects_header_4: 'Emotional Analysis of Self-Talk and Positive Transformation for Recording and Feedback of Latent Emotions',
projects_description_4: "This study aims to develop an application that records and analyzes unconscious self-talk to promote emotional awareness and positive transformation. The proposed method converts audio recordings into mel spectrograms and uses a CNN model to classify the input as either \"self-talk\" or \"conversation,\" with its accuracy evaluated.",
projects_header_5: 'Visualization system for audience sentiment based on comments on live streaming',
projects_description_5: "The system estimates positive and negative sentiments in the comments section of twitch.tv, a live streaming platform, and visualizes them. The visualization system is displayed on the streaming service, and the distributors can analyze and improve their own services based on the information. Through these means, we aim to provide viewers with a more authentic and unifying delivery experience.",
projects_header_6: 'FLECS',
projects_description_6: "This study aims to develop a chatbot that simulates a psychological counselor by fine-tuning a pre-trained model for counseling purposes. To address privacy concerns, federated learning is employed and its effectiveness is evaluated in comparison with centralized learning.",
joinus_required_header: 'Required',
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about_shift: 'SHIFT（System for Human and Intelligence towards Future Transformation）研究グループは、人間の生活の未来的な変容を形づくり、それを支えるAIシステムの探究と設計を目的としています。今後10〜15年にわたる人々の暮らしの変化を見据え、未来における新しいウェルビーイングの形を追究し、急速に変化していく社会との調和を高める知的技術の開発を目指します。',
projects_header_1: 'ライフログサービスにおける行動変容に向けた適応的プッシュ通知',
projects_description_1: '本研究では、ユーザーのライフログ入力を促進するための効果的な情報提示方法を検討した。(a)個人の特性に応じた文言の調整、(b)身体活動に応じたタイミングの調整、(c)これらの調整の組み合わせ、の3つで実証実験を行った。',
projects_header_2: 'EmoGO',
projects_description_2: 'EmoGOは、アイトラッキングデータをもとに感情を推定し、視界内の物体を検出することで、見た物体と想起される感情を記録するシステムである。システムの有効性を確認するために、慶應義塾大学湘南藤沢キャンパスと寒川神社にてユーザ実験を行った。',
projects_header_3: 'スマートフォンを利用したアクティビティと感情を考慮した音楽ストリーミング推薦システム',
projects_description_3: '人間の活動や感情状態に基づいて音楽を推薦するスマートフォンベースのシステム。このシステムには、活動認識、感情検出、音楽推薦の3つのモジュールがある。機械学習によりスマートフォンの信号を解釈し、協調フィルタリングにより音楽を推薦する。',
projects_header_4: '独り言の感情分析とポジティブ変換による潜在的感情の記録とフィードバック',
projects_description_4: '本研究は、無意識に発せられる独り言を記録・分析し、ユーザーの感情理解とポジティブな変容を促すアプリケーションの開発を目的とする。音声データをメルスペクトログラムに変換し、CNNモデルにより「独り言」と「会話」を分類する手法を提案し、その精度を検証した。',
projects_header_5: 'ライブストリーミングへのコメントに基づく視聴者感情の可視化システム',
projects_description_5: 'ライブストリーミングプラットフォームtwitch.tvのコメント欄におけるポジティブ・ネガティブな感情を推定し、その結果を可視化するシステムを提案する。可視化された感情データを配信上に表示し、分析・改善することで、一体感のある配信体験をしてもらうことを目的とする。',
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projects_description_6: '本研究は、心理カウンセラーを模倣するチャットボットの開発を目的とし、事前学習モデルをカウンセリング用途にFine-tuningする。プライバシー保護の観点からFederated Learning を用い、Centralized 学習と比較しつつ、その有効性を検証した。',
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