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題名 探討情緒對偶然驚喜推薦系統的設計與影響
The design and influence of emotion on serendipity recommender system
作者 郭蕎銥
Guo, Ciao-Yi
貢獻者 林怡伶
Lin, Yi-Ling
郭蕎銥
Guo, Ciao-Yi
關鍵詞 情緒
偶然驚喜推薦系統
好奇心
使用者偏好
情緒識別
Emotion
Serendipity recommender system
Curiosity
User preference
Emotion Recognition
日期 2023
上傳時間 1-Sep-2023 14:52:45 (UTC+8)
摘要 傳統推薦系統大多只追求推薦的準確性，根據使用者的歷史行為和偏好，推薦其相關物品，這樣的推薦雖然能減輕資訊過量的問題，幫助使用者做出合適的決定。然而，卻導致過度專業化，讓用戶覺得缺乏新鮮感，對系統的推薦失去興趣。根據過去研究，在系統引入偶然驚喜能夠有效解決過度專業化的問題並提高滿意。為了解決這個問題，推薦系統可以引入偶然驚喜的推薦機制。好奇心是促使人們探索行為的重要因素，促進人們對偶然驚喜的探索。現行的偶然驚喜推薦系統多基於使用者的好奇心，推薦可能出乎使用者意料、但又符合使用者興趣和偏好的物品。除了個性外，情緒也會影響人的心情，而心情會影響人的決策。情緒會隨著時間變化，被視為是使用者短期偏好的相關因素，且會影響使用者對偶然驚喜的想法跟接受度。然而，以往的偶然驚喜推薦系統很少考慮用戶的情緒。本研究透過提供使用者不同偶然驚喜程度的推薦列表，探討情緒是否影響使用者對偶然驚喜推薦策略的接受傾向，了解情緒與使用者對偶然驚喜推薦偏好的關係。研究結果指出，除了好奇心外，情緒也會影響使用者對偶然驚喜推薦策略的偏好與接受傾向。因此，未來的偶然驚喜推薦系統，除了基於好奇心，也可以納入使用者的情緒，去決定推薦的偶然驚喜程度，以提升使用者對推薦的滿意度。
Recommender systems can eliminate users’ information overload and help users make proper decisions by suggesting items based on users’ preferences. However, most current recommender systems overemphasize accuracy. That might cause an overspecialization problem and even lose users’ interest. To overcome the problem, the recommender system can suggest serendipitous items. Exploratory behavior is a facilitator of serendipity. Curiosity, a personality trait, is the most considered characteristics for people’s explorative behaviors and serendipity recommender system. Other than personality, mood is also affected by emotion and influences people’s decision-making. Emotion changes over time, which can be regarded as a relevant factor to short-term user preference and influence users’ thoughts and behavior toward serendipitous information. However, previous serendipity recommender system rarely takes users’ emotion into account. In this research, we proposed serendipity recommendation with different serendipity level to discuss whether emotion matter for the serendipity recommender system and know the relationship between emotion and users’ serendipity preference toward serendipity recommendation list. The result shows that users’ emotion has significant influence on their serendipity preference. Therefore, we believe that incorporating user’s emotion into future serendipity recommendations would improve users’ satisfaction.
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描述 碩士
國立政治大學
資訊管理學系
110356015
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110356015
資料類型 thesis
dc.contributor.advisor 林怡伶zh_TW
dc.contributor.advisor Lin, Yi-Lingen_US
dc.contributor.author (Authors) 郭蕎銥zh_TW
dc.contributor.author (Authors) Guo, Ciao-Yien_US
dc.creator (作者) 郭蕎銥zh_TW
dc.creator (作者) Guo, Ciao-Yien_US
dc.date (日期) 2023en_US
dc.date.accessioned 1-Sep-2023 14:52:45 (UTC+8)-
dc.date.available 1-Sep-2023 14:52:45 (UTC+8)-
dc.date.issued (上傳時間) 1-Sep-2023 14:52:45 (UTC+8)-
dc.identifier (Other Identifiers) G0110356015en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/146885-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理學系zh_TW
dc.description (描述) 110356015zh_TW
dc.description.abstract (摘要) 傳統推薦系統大多只追求推薦的準確性，根據使用者的歷史行為和偏好，推薦其相關物品，這樣的推薦雖然能減輕資訊過量的問題，幫助使用者做出合適的決定。然而，卻導致過度專業化，讓用戶覺得缺乏新鮮感，對系統的推薦失去興趣。根據過去研究，在系統引入偶然驚喜能夠有效解決過度專業化的問題並提高滿意。為了解決這個問題，推薦系統可以引入偶然驚喜的推薦機制。好奇心是促使人們探索行為的重要因素，促進人們對偶然驚喜的探索。現行的偶然驚喜推薦系統多基於使用者的好奇心，推薦可能出乎使用者意料、但又符合使用者興趣和偏好的物品。除了個性外，情緒也會影響人的心情，而心情會影響人的決策。情緒會隨著時間變化，被視為是使用者短期偏好的相關因素，且會影響使用者對偶然驚喜的想法跟接受度。然而，以往的偶然驚喜推薦系統很少考慮用戶的情緒。本研究透過提供使用者不同偶然驚喜程度的推薦列表，探討情緒是否影響使用者對偶然驚喜推薦策略的接受傾向，了解情緒與使用者對偶然驚喜推薦偏好的關係。研究結果指出，除了好奇心外，情緒也會影響使用者對偶然驚喜推薦策略的偏好與接受傾向。因此，未來的偶然驚喜推薦系統，除了基於好奇心，也可以納入使用者的情緒，去決定推薦的偶然驚喜程度，以提升使用者對推薦的滿意度。zh_TW
dc.description.abstract (摘要) Recommender systems can eliminate users’ information overload and help users make proper decisions by suggesting items based on users’ preferences. However, most current recommender systems overemphasize accuracy. That might cause an overspecialization problem and even lose users’ interest. To overcome the problem, the recommender system can suggest serendipitous items. Exploratory behavior is a facilitator of serendipity. Curiosity, a personality trait, is the most considered characteristics for people’s explorative behaviors and serendipity recommender system. Other than personality, mood is also affected by emotion and influences people’s decision-making. Emotion changes over time, which can be regarded as a relevant factor to short-term user preference and influence users’ thoughts and behavior toward serendipitous information. However, previous serendipity recommender system rarely takes users’ emotion into account. In this research, we proposed serendipity recommendation with different serendipity level to discuss whether emotion matter for the serendipity recommender system and know the relationship between emotion and users’ serendipity preference toward serendipity recommendation list. The result shows that users’ emotion has significant influence on their serendipity preference. Therefore, we believe that incorporating user’s emotion into future serendipity recommendations would improve users’ satisfaction.en_US
dc.description.tableofcontents TABLES I
FIGURES II
CHAPTER 1 INTRODUCTION 1
1.1 BACKGROUND AND MOTIVATION 1
CHAPTER 2 LITERATURE REVIEW 3
2.1 SERENDIPITY 3
2.2 FROM CURIOSITY TO EMOTION 4
2.3 BROADEN-AND-BUILD THEORY 7
CHAPTER 3 RESEARCH DESIGN 11
3.1 DATASET 11
3.2 RECOMMENDER ALGORITHM 11
3.3 MANIPULATION - EMOTION STIMULI 13
3.4 EMOTION RECOGNITION METHOD 14
3.5 RECOMMENDATION EVALUATION 18
3.6 EXPERIMENTAL PARTICIPANTS 19
3.7 DESIGN AND PROCEDURE 20
3.8 HYPOTHESIS 25
CHAPTER 4 ANALYSIS OF RESULTS 28
4.1 ANALYSIS OF EMOTION ON SERENDIPITY 29
4.2 ANALYSIS OF POSITIVE AND NEGATIVE EMOTION ON SERENDIPITY 30
4.3 FURTHER ANALYSIS RESULT 33
CHAPTER 5 DISCUSSION AND CONTRIBUTION 34
5.1 DISCUSSION 34
5.2 THEORETICAL CONTRIBUTIONS 35
5.3 PRACTICAL CONTRIBUTIONS 36
CHAPTER 6 LIMITATIONS AND FUTURE WORK 38
REFERENCE 39
APPENDIX 1 – THE CURIOSITY AND EXPLORATION INVENTORY-II 48
APPENDIX 2 – SELF-ASSESSMENT MANIKIN (SAM) 48		zh_TW
dc.format.extent 2275487 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110356015en_US
dc.subject (關鍵詞) 情緒zh_TW
dc.subject (關鍵詞) 偶然驚喜推薦系統zh_TW
dc.subject (關鍵詞) 好奇心zh_TW
dc.subject (關鍵詞) 使用者偏好zh_TW
dc.subject (關鍵詞) 情緒識別zh_TW
dc.subject (關鍵詞) Emotionen_US
dc.subject (關鍵詞) Serendipity recommender systemen_US
dc.subject (關鍵詞) Curiosityen_US
dc.subject (關鍵詞) User preferenceen_US
dc.subject (關鍵詞) Emotion Recognitionen_US
dc.title (題名) 探討情緒對偶然驚喜推薦系統的設計與影響zh_TW
dc.title (題名) The design and influence of emotion on serendipity recommender systemen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Abbas, F., & Niu, X. (2019). One size does not fit all: Modeling users’ personal curiosity in recommender systems. ArXivorg.
Abbas, R., Hassan, G. M., Al-Razgan, M., Zhang, M., Amran, G. A., Al Bakhrani, A. A., Alfakih, T., Al-Sanabani, H., & Rahman, S. M. M. (2022). A serendipity-oriented personalized trip recommendation model. Electronics, 11(10), 1660.
Abdul, A., Chen, J., Liao, H.-Y., & Chang, S.-H. (2018). An emotion-aware personalized music recommendation system using a convolutional neural networks approach. Applied Sciences, 8(7), 1103.
Adamopoulos, P., & Tuzhilin, A. (2014). On unexpectedness in recommender systems: Or how to better expect the unexpected. ACM Transactions on Intelligent Systems and Technology (TIST), 5(4), 1–32.
Alrihaili, A., Alsaedi, A., Albalawi, K., & Syed, L. (2019). Music recommender system for users based on emotion detection through facial features. In 2019 12th International Conference on Developments in eSystems Engineering (DeSE). IEEE.
Altan, A., & Karasu, S. (2019). The effect of kernel values in support vector machine to forecasting performance of financial time series. The Journal of Cognitive Systems, 4, 17–21.
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