{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:21:06Z","timestamp":1750220466096,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":7,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,9,24]],"date-time":"2021-09-24T00:00:00Z","timestamp":1632441600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,9,24]]},"DOI":"10.1145\/3482632.3484054","type":"proceedings-article","created":{"date-parts":[[2021,11,22]],"date-time":"2021-11-22T17:26:28Z","timestamp":1637601988000},"page":"1853-1856","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Forecast of Foreign Exchange Rate Trend Based on Time Series Similarity"],"prefix":"10.1145","author":[{"given":"Yaxin","family":"Qu","sequence":"first","affiliation":[{"name":"North China University of Technology, China"}]},{"given":"Kaixuan","family":"Zhao","sequence":"additional","affiliation":[{"name":"North China University of Technology, China"}]}],"member":"320","published-online":{"date-parts":[[2021,11,22]]},"reference":[{"issue":"01","key":"e_1_3_2_1_1_1","first-page":"56","article-title":"Trend Turning Point Extraction Algorithm for Time Series Data [J]","volume":"44","author":"Han Xing","year":"2018","unstructured":"Xing Han , Shi Xiaoda , Sun Lianying , Ge Na . Trend Turning Point Extraction Algorithm for Time Series Data [J] . Computer Engineering , 2018 , 44 ( 01 ): 56 - 61 + 68. Xing Han, Shi Xiaoda, Sun Lianying, Ge Na. Trend Turning Point Extraction Algorithm for Time Series Data [J]. Computer Engineering, 2018, 44 (01): 56-61 + 68.","journal-title":"Computer Engineering"},{"key":"e_1_3_2_1_2_1","volume-title":"Research on Shape-Based Time Series Similarity [D]","author":"Rui Wang","year":"2017","unstructured":"Wang Rui . Research on Shape-Based Time Series Similarity [D] . Anhui University , 2017 . Wang Rui. Research on Shape-Based Time Series Similarity [D]. Anhui University, 2017."},{"issue":"01","key":"e_1_3_2_1_3_1","first-page":"1","article-title":"Review on similarity measurements in time series data mining [J]","volume":"32","author":"Haiyan Chen","year":"2017","unstructured":"Chen Haiyan , Liu Chenhui , Sun Bo . Review on similarity measurements in time series data mining [J] . Control and Decision , 2017 , 32 ( 01 ): 1 - 11 . Chen Haiyan, Liu Chenhui, Sun Bo. Review on similarity measurements in time series data mining [J]. Control and Decision, 2017, 32 (01): 1-11.","journal-title":"Control and Decision"},{"issue":"06","key":"e_1_3_2_1_4_1","first-page":"109","article-title":"The Empirical Study on Fractal Price Behavior of Stock Indexes [J]","volume":"2013","author":"Wei Zheng","unstructured":"Zheng Wei . The Empirical Study on Fractal Price Behavior of Stock Indexes [J] . Technoeconomics & Management Research , 2013 ( 06 ): 109 - 113 . Zheng Wei. The Empirical Study on Fractal Price Behavior of Stock Indexes [J]. Technoeconomics & Management Research, 2013 (06): 109-113.","journal-title":"Technoeconomics & Management Research"},{"key":"e_1_3_2_1_5_1","volume-title":"Trend feature extraction method based on important points in time series [J]","author":"Qian Zhou","year":"2007","unstructured":"Zhou Qian , Wu Tiejun . Trend feature extraction method based on important points in time series [J] . Journal of Zhejiang University (Engineering Science) , 2007 (11): 1782-1787. Zhou Qian, Wu Tiejun. Trend feature extraction method based on important points in time series [J]. Journal of Zhejiang University (Engineering Science), 2007 (11): 1782-1787."},{"key":"e_1_3_2_1_6_1","volume-title":"Application of deep learning in quantitative trading [D]","author":"Xue Zhao","year":"2019","unstructured":"Zhao Xue . Application of deep learning in quantitative trading [D] . North China University of Technology , 2019 . Zhao Xue. Application of deep learning in quantitative trading [D]. North China University of Technology, 2019."},{"issue":"08","key":"e_1_3_2_1_7_1","first-page":"1345","article-title":"Review on dynamic time warping in time series data mining [J]","volume":"33","author":"Hailin Li","year":"2018","unstructured":"Li Hailin , Liang ye, Wang Shaochun . Review on dynamic time warping in time series data mining [J] . Control and Decision , 2018 , 33 ( 08 ): 1345 - 1353 . Li Hailin, Liang ye, Wang Shaochun. Review on dynamic time warping in time series data mining [J]. Control and Decision, 2018, 33 (08): 1345-1353.","journal-title":"Control and Decision"}],"event":{"acronym":"ICISCAE 2021","name":"ICISCAE 2021: 2021 IEEE 4th International Conference on Information Systems and Computer Aided Education","location":"Dalian China"},"container-title":["2021 4th International Conference on Information Systems and Computer Aided Education"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3482632.3484054","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3482632.3484054","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:48:20Z","timestamp":1750193300000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3482632.3484054"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,24]]},"references-count":7,"alternative-id":["10.1145\/3482632.3484054","10.1145\/3482632"],"URL":"https:\/\/doi.org\/10.1145\/3482632.3484054","relation":{},"subject":[],"published":{"date-parts":[[2021,9,24]]},"assertion":[{"value":"2021-11-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}