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Titlebook: Case-Based Reasoning Research and Development; 29th International C Antonio A. Sánchez-Ruiz,Michael W. Floyd Conference proceedings 2021 Sp

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書目名稱Case-Based Reasoning Research and Development
副標(biāo)題29th International C
編輯Antonio A. Sánchez-Ruiz,Michael W. Floyd
視頻videohttp://file.papertrans.cn/223/222327/222327.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Case-Based Reasoning Research and Development; 29th International C Antonio A. Sánchez-Ruiz,Michael W. Floyd Conference proceedings 2021 Sp
描述This book constitutes the proceedings of the 29th International Conference on Case-Based Reasoning, ICCBR 2021, which took place in Salamanca, Spain, during September 13-16, 2021.?.The 21 papers presented in this volume were carefully reviewed and selected from 85 submissions. They deal with AI and related research focusing on comparison and integration of CBR with other AI methods such as deep learning architectures, reinforcement learning, lifelong learning, and eXplainable AI (XAI)..
出版日期Conference proceedings 2021
關(guān)鍵詞artificial intelligence; case based reasoning; cognition; computer vision; correlation analysis; data min
版次1
doihttps://doi.org/10.1007/978-3-030-86957-1
isbn_softcover978-3-030-86956-4
isbn_ebook978-3-030-86957-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

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News Recommendation with CF-IDF+istory in direct recommendation of recipes and meal planning, as well as conversational exploration of the possibilities for new food items. But more limited attention has been given to incorporating diversity outcomes as a primary factor in conversational critique for exploration. Critiquing as a m
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Lecture Notes in Computer Sciences of this type of training is the design of the scripts of the sessions, usually called “scenarios”. Currently, civil aviation authorities are advocating a customization of the flight training scenarios based on the specific needs of each pilot, which makes their creation a very demanding task in ti
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The Relational Process Structure influence trading volume and prices. Nevertheless it has proven to be an attractive target for machine learning research because of the potential for even modest levels of prediction accuracy to deliver significant benefits. In this paper, we describe a case-based reasoning approach to predicting s
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