每年專案
摘要
This study proposes a framework for generating customized trend lines that consider user preferences and input time series shapes. The existing trend estimators fail to capture individual needs and application domain requirements. The proposed framework obtains users’ preferred trends by asking users to draw trend lines on sample datasets. The experiments and case studies demonstrate the effectiveness of the model. Code and dataset are available at https://github.com/Anthony860810/Generating-Personalized-Trend-Line-Based-on-Few-Labelings-from-One-Individual.
原文 | ???core.languages.en_GB??? |
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主出版物標題 | Advances in Knowledge Discovery and Data Mining - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Proceedings |
編輯 | Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng |
發行者 | Springer Science and Business Media Deutschland GmbH |
頁面 | 276-288 |
頁數 | 13 |
ISBN(列印) | 9783031333828 |
DOIs | |
出版狀態 | 已出版 - 2023 |
事件 | 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023 - Osaka, Japan 持續時間: 25 5月 2023 → 28 5月 2023 |
出版系列
名字 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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卷 | 13938 LNCS |
ISSN(列印) | 0302-9743 |
ISSN(電子) | 1611-3349 |
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???event.eventtypes.event.conference??? | 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023 |
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國家/地區 | Japan |
城市 | Osaka |
期間 | 25/05/23 → 28/05/23 |
指紋
深入研究「Petrel: Personalized Trend Line Estimation with Limited Labels from One Individual」主題。共同形成了獨特的指紋。專案
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