{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T07:54:12Z","timestamp":1767772452881,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":46,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,6,27]],"date-time":"2023-06-27T00:00:00Z","timestamp":1687824000000},"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":[[2023,6,27]]},"DOI":"10.1145\/3583678.3596888","type":"proceedings-article","created":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T20:21:36Z","timestamp":1687810896000},"page":"80-90","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Practical Forecasting of Cryptocoins Timeseries using Correlation Patterns"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9726-7075","authenticated-orcid":false,"given":"Pasquale","family":"De Rosa","sequence":"first","affiliation":[{"name":"University of Neuch\u00e2tel, Switzerland, Neuch\u00e2tel, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1574-6721","authenticated-orcid":false,"given":"Pascal","family":"Felber","sequence":"additional","affiliation":[{"name":"University of Neuch\u00e2tel, Switzerland, Neuch\u00e2tel, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1493-6603","authenticated-orcid":false,"given":"Valerio","family":"Schiavoni","sequence":"additional","affiliation":[{"name":"University of Neuch\u00e2tel, Switzerland, Neuch\u00e2tel, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,6,27]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-32833-1_401"},{"volume-title":"Retrieved","year":"2023","key":"e_1_3_2_1_2_1","unstructured":"2015. Higgs Boson Machine Learning Challenge . Retrieved May 23, 2023 from https:\/\/www.kaggle.com\/c\/higgs-boson\/discussion\/10998 2015. Higgs Boson Machine Learning Challenge. Retrieved May 23, 2023 from https:\/\/www.kaggle.com\/c\/higgs-boson\/discussion\/10998"},{"key":"e_1_3_2_1_3_1","unstructured":"2023. Binance Exchange. Retrieved May 23 2023 from https:\/\/www.binance.com  2023. Binance Exchange. Retrieved May 23 2023 from https:\/\/www.binance.com"},{"key":"e_1_3_2_1_4_1","unstructured":"2023. Coinbase Exchange. Retrieved May 23 2023 from https:\/\/www.coinbase.com  2023. Coinbase Exchange. Retrieved May 23 2023 from https:\/\/www.coinbase.com"},{"volume-title":"Retrieved","year":"2023","key":"e_1_3_2_1_5_1","unstructured":"2023. CoinMarketCap Web Service . Retrieved May 23, 2023 from https:\/\/coinmarketcap.com 2023. CoinMarketCap Web Service. Retrieved May 23, 2023 from https:\/\/coinmarketcap.com"},{"volume-title":"Retrieved","year":"2023","key":"e_1_3_2_1_6_1","unstructured":"2023. International Monetary Fund . Retrieved May 23, 2023 from https:\/\/www.imf.org\/en\/Publications\/WEO 2023. International Monetary Fund. Retrieved May 23, 2023 from https:\/\/www.imf.org\/en\/Publications\/WEO"},{"key":"e_1_3_2_1_7_1","unstructured":"2023. Kraken Exchange. Retrieved May 23 2023 from https:\/\/www.kraken.com  2023. Kraken Exchange. Retrieved May 23 2023 from https:\/\/www.kraken.com"},{"volume-title":"Retrieved","year":"2023","key":"e_1_3_2_1_8_1","unstructured":"2023. UniSwap Decentralixed Exchange . Retrieved May 23, 2023 from https:\/\/uniswap.org 2023. UniSwap Decentralixed Exchange. Retrieved May 23, 2023 from https:\/\/uniswap.org"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-1694-0_15"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.frl.2019.04.019"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3492321.3519584"},{"key":"e_1_3_2_1_12_1","volume-title":"Ljung","author":"Box George E.P.","year":"2015","unstructured":"George E.P. Box , Gwilym M. Jenkins , Gregory C. Reinsel , and Greta M . Ljung . 2015 . Time Series Analysis: Forecasting and Control. Wiley . https:\/\/www.wiley.com\/en-us\/Time+Series+Analysis:+Forecasting+and+Control,+5th+Edition-p-9781118675021 George E.P. Box, Gwilym M. Jenkins, Gregory C. Reinsel, and Greta M. Ljung. 2015. Time Series Analysis: Forecasting and Control. Wiley. https:\/\/www.wiley.com\/en-us\/Time+Series+Analysis:+Forecasting+and+Control,+5th+Edition-p-9781118675021"},{"key":"e_1_3_2_1_13_1","unstructured":"Vitalik Buterin et al. 2013. Ethereum white paper. GitHub repository 1 (2013) 22--23. https:\/\/github.com\/ethereum\/wiki\/wiki\/White-Paper  Vitalik Buterin et al. 2013. Ethereum white paper. GitHub repository 1 (2013) 22--23. https:\/\/github.com\/ethereum\/wiki\/wiki\/White-Paper"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2020.101130"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/W14-4012"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-75959-3"},{"key":"e_1_3_2_1_18_1","volume-title":"Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: journal of the Econometric Society","author":"Dickey David A","year":"1981","unstructured":"David A Dickey and Wayne A Fuller . 1981. Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: journal of the Econometric Society ( 1981 ), 1057--1072. David A Dickey and Wayne A Fuller. 1981. Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: journal of the Econometric Society (1981), 1057--1072."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.18178\/ijmlc.2017.7.5.632"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.5555\/1953048.2021068"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.2469\/faj.v21.n5.55"},{"volume-title":"Deep Learning","author":"Goodfellow Ian","key":"e_1_3_2_1_22_1","unstructured":"Ian Goodfellow , Yoshua Bengio , and Aaron Courville . 2016. Deep Learning . MIT Press . http:\/\/www.deeplearningbook.org. Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2016. Deep Learning. MIT Press. http:\/\/www.deeplearningbook.org."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.2307\/1912791"},{"volume-title":"Time series analysis","author":"Hamilton James Douglas","key":"e_1_3_2_1_24_1","unstructured":"James Douglas Hamilton . 2020. Time series analysis . Princeton University Press . James Douglas Hamilton. 2020. Time series analysis. Princeton University Press."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4614-7138-7"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.frl.2018.10.005"},{"key":"e_1_3_2_1_28_1","volume-title":"Garnett (Eds.)","volume":"30","author":"Ke Guolin","year":"2017","unstructured":"Guolin Ke , Qi Meng , Thomas Finley , Taifeng Wang , Wei Chen , Weidong Ma , Qiwei Ye , and Tie-Yan Liu . 2017 . LightGBM: A Highly Efficient Gradient Boosting Decision Tree. In Advances in Neural Information Processing Systems, I. Guyon, U. Von Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R . Garnett (Eds.) , Vol. 30 . Curran Associates, Inc. https:\/\/proceedings.neurips.cc\/paper\/ 2017\/file\/6449f44a102fde848669bdd9eb6b76fa-Paper.pdf Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, and Tie-Yan Liu. 2017. LightGBM: A Highly Efficient Gradient Boosting Decision Tree. In Advances in Neural Information Processing Systems, I. Guyon, U. Von Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett (Eds.), Vol. 30. Curran Associates, Inc. https:\/\/proceedings.neurips.cc\/paper\/2017\/file\/6449f44a102fde848669bdd9eb6b76fa-Paper.pdf"},{"key":"e_1_3_2_1_29_1","volume-title":"Kingma and Jimmy Ba","author":"Diederik","year":"2015","unstructured":"Diederik P. Kingma and Jimmy Ba . 2015 . Adam : A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7--9, 2015, Conference Track Proceedings, Yoshua Bengio and Yann LeCun (Eds .). http:\/\/arxiv.org\/abs\/1412.6980 Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7--9, 2015, Conference Track Proceedings, Yoshua Bengio and Yann LeCun (Eds.). http:\/\/arxiv.org\/abs\/1412.6980"},{"key":"e_1_3_2_1_30_1","volume-title":"The predictive power of public Twitter sentiment for forecasting cryptocurrency prices. Journal of International Financial Markets, Institutions and Money 65","author":"Kraaijeveld Olivier","year":"2020","unstructured":"Olivier Kraaijeveld and Johannes De Smedt . 2020. The predictive power of public Twitter sentiment for forecasting cryptocurrency prices. Journal of International Financial Markets, Institutions and Money 65 ( 2020 ). Olivier Kraaijeveld and Johannes De Smedt. 2020. The predictive power of public Twitter sentiment for forecasting cryptocurrency prices. Journal of International Financial Markets, Institutions and Money 65 (2020)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40854-019-0143-3"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/0304-4076(92)90104-Y"},{"key":"e_1_3_2_1_33_1","article-title":"Time-series forecasting with deep learning: a survey","volume":"379","author":"Lim Bryan","year":"2021","unstructured":"Bryan Lim and Stefan Zohren . 2021 . Time-series forecasting with deep learning: a survey . Philosophical Transactions of the Royal Society A 379 , 2194 (2021). Bryan Lim and Stefan Zohren. 2021. Time-series forecasting with deep learning: a survey. Philosophical Transactions of the Royal Society A 379, 2194 (2021).","journal-title":"Philosophical Transactions of the Royal Society A"},{"key":"e_1_3_2_1_34_1","volume-title":"Classification and regression trees","author":"Loh Wei-Yin","year":"2011","unstructured":"Wei-Yin Loh . 2011. Classification and regression trees . Wiley interdisciplinary reviews: data mining and knowledge discovery 1, 1 ( 2011 ), 14--23. Wei-Yin Loh. 2011. Classification and regression trees. Wiley interdisciplinary reviews: data mining and knowledge discovery 1, 1 (2011), 14--23."},{"key":"e_1_3_2_1_35_1","volume-title":"Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review","author":"Nakamoto Satoshi","year":"2008","unstructured":"Satoshi Nakamoto . 2008 . Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review (2008), 212--260. Satoshi Nakamoto. 2008. Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review (2008), 212--260."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bir.2020.10.006"},{"key":"e_1_3_2_1_37_1","volume-title":"Proceedings of the 32nd International Conference on Neural Information Processing Systems","author":"Prokhorenkova Liudmila","year":"2018","unstructured":"Liudmila Prokhorenkova , Gleb Gusev , Aleksandr Vorobev , Anna Veronika Dorogush , and Andrey Gulin . 2018 . CatBoost: Unbiased Boosting with Categorical Features . In Proceedings of the 32nd International Conference on Neural Information Processing Systems ( Montr\u00e9al, Canada) (NIPS'18). Curran Associates Inc., Red Hook, NY, USA, 6639--6649. Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, and Andrey Gulin. 2018. CatBoost: Unbiased Boosting with Categorical Features. In Proceedings of the 32nd International Conference on Neural Information Processing Systems (Montr\u00e9al, Canada) (NIPS'18). Curran Associates Inc., Red Hook, NY, USA, 6639--6649."},{"key":"e_1_3_2_1_39_1","volume-title":"Mehmet Ugur Gudelek, and Ahmet Murat Ozbayoglu","author":"Sezer Omer Berat","year":"2020","unstructured":"Omer Berat Sezer , Mehmet Ugur Gudelek, and Ahmet Murat Ozbayoglu . 2020 . Financial time series forecasting with deep learning: A systematic literature review: 2005--2019. Applied soft computing 90 (2020), 106181. Omer Berat Sezer, Mehmet Ugur Gudelek, and Ahmet Murat Ozbayoglu. 2020. Financial time series forecasting with deep learning: A systematic literature review: 2005--2019. Applied soft computing 90 (2020), 106181."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3457557"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.12.084"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.5555\/1088844"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2018.00227"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1016\/0304-4076(94)01616-8"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1089\/big.2020.0159"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1090\/S0002-9947-1943-0012401-3"},{"key":"e_1_3_2_1_47_1","volume-title":"Zeiler and Rob Fergus","author":"Matthew","year":"2014","unstructured":"Matthew D. Zeiler and Rob Fergus . 2014 . Visualizing and Understanding Convolutional Networks. In Computer Vision - ECCV 2014, David Fleet, Tomas Pajdla, Bernt Schiele, and Tinne Tuytelaars (Eds.). Springer International Publishing , Cham, 818--833. Matthew D. Zeiler and Rob Fergus. 2014. Visualizing and Understanding Convolutional Networks. In Computer Vision - ECCV 2014, David Fleet, Tomas Pajdla, Bernt Schiele, and Tinne Tuytelaars (Eds.). Springer International Publishing, Cham, 818--833."}],"event":{"name":"DEBS '23: 17th ACM International Conference on Distributed and Event-based Systems","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGSOFT ACM Special Interest Group on Software Engineering"],"location":"Neuchatel Switzerland","acronym":"DEBS '23"},"container-title":["Proceedings of the 17th ACM International Conference on Distributed and Event-based Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3583678.3596888","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:37:55Z","timestamp":1750178275000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3583678.3596888"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,27]]},"references-count":46,"alternative-id":["10.1145\/3583678.3596888","10.1145\/3583678"],"URL":"https:\/\/doi.org\/10.1145\/3583678.3596888","relation":{},"subject":[],"published":{"date-parts":[[2023,6,27]]},"assertion":[{"value":"2023-06-27","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}