Construction of dynamic update and adaptive prediction model for user profile based on time series analysis

[1] Gu, H., Wang, J., Wang, Z., Zhuang, B., & Su, F. (2018, July). Modeling of user portrait through social media. In 2018 IEEE international conference on multimedia and expo (ICME) (pp. 1-6). IEEE. Gu H. Wang J. Wang Z. Zhuang B. Su F. ( 2018 , July ). Modeling of user portrait through social media . In 2018 IEEE international conference on multimedia and expo (ICME) (pp. 1 - 6 ). IEEE . Search in Google Scholar

[2] Chen, Y., He, J., Wei, W., Zhu, N., & Yu, C. (2021). A multi-model approach for user portrait. Future Internet, 13(6), 147. Chen Y. He J. Wei W. Zhu N. Yu C. ( 2021 ). A multi-model approach for user portrait . Future Internet , 13 ( 6 ), 147 . Search in Google Scholar

[3] Yuan, T. (2022, July). User portrait based on artificial intelligence. In International Conference on Frontier Computing (pp. 359-366). Singapore: Springer Nature Singapore. Yuan T. ( 2022 , July ). User portrait based on artificial intelligence . In International Conference on Frontier Computing (pp. 359 - 366 ). Singapore: Springer Nature Singapore . Search in Google Scholar

[4] Li, G., Chen, W., Yan, X., & Wang, L. (2022). Modeling and analysis of group user portrait through WeChat mini program. Wireless Communications and Mobile Computing, 2022(1), 2515962. Li G. Chen W. Yan X. Wang L. ( 2022 ). Modeling and analysis of group user portrait through WeChat mini program . Wireless Communications and Mobile Computing , 2022 ( 1 ), 2515962 . Search in Google Scholar

[5] Sun, Y., & Chai, R. (2020). An Early-Warning Model for Online Learners Based on User Portrait. Ingénierie des Systèmes d’Information, 25(4). Sun Y. Chai R. ( 2020 ). An Early-Warning Model for Online Learners Based on User Portrait . Ingénierie des Systèmes d’Information , 25 ( 4 ). Search in Google Scholar

[6] Chen, T., Yin, X., Peng, L., Rong, J., Yang, J., & Cong, G. (2021). Monitoring and recognizing enterprise public opinion from high-risk users based on user portrait and random forest algorithm. Axioms, 10(2), 106. Chen T. Yin X. Peng L. Rong J. Yang J. Cong G. ( 2021 ). Monitoring and recognizing enterprise public opinion from high-risk users based on user portrait and random forest algorithm . Axioms , 10 ( 2 ), 106 . Search in Google Scholar

[7] Tang, Y., Li, S., Song, W., Zhou, C., & Niu, Z. (2021, August). Service recommendation based on dynamic user portrait: an integrated approach. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (Vol. 85376, p. V002T02A056). American Society of Mechanical Engineers. Tang Y. Li S. Song W. Zhou C. Niu Z. ( 2021 , August ). Service recommendation based on dynamic user portrait: an integrated approach . In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (Vol. 85376 , p. V002T02A056 ). American Society of Mechanical Engineers . Search in Google Scholar

[8] Hamilton, J. D. (2020). Time series analysis. Princeton university press. Hamilton J. D. ( 2020 ). Time series analysis . Princeton university press . Search in Google Scholar

[9] Fulcher, B. D. (2018). Feature-based time-series analysis. In Feature engineering for machine learning and data analytics (pp. 87-116). CRC press. Fulcher B. D. ( 2018 ). Feature-based time-series analysis . In Feature engineering for machine learning and data analytics (pp. 87 - 116 ). CRC press . Search in Google Scholar

[10] Kumar, R., Jain, A., Tripathi, A. K., & Tyagi, S. (2021, January). Covid-19 outbreak: An epidemic analysis using time series prediction model. In 2021 11th international conference on cloud computing, data science & engineering (Confluence) (pp. 1090-1094). IEEE. Kumar R. Jain A. Tripathi A. K. Tyagi S. ( 2021 , January ). Covid-19 outbreak: An epidemic analysis using time series prediction model . In 2021 11th international conference on cloud computing, data science & engineering (Confluence) (pp. 1090 - 1094 ). IEEE . Search in Google Scholar

[11] Rayskin, V. (2020, December). Multivariate time series approximation by multiple trajectories of a dynamical system. Applications to internet traffic and COVID-19 data. In AIP Conference Proceedings (Vol. 2302, No. 1). AIP Publishing. Rayskin V. ( 2020 , December ). Multivariate time series approximation by multiple trajectories of a dynamical system . Applications to internet traffic and COVID-19 data. In AIP Conference Proceedings (Vol. 2302 , No. 1 ). AIP Publishing . Search in Google Scholar

[12] Min, T., & Cai, W. (2022). Portrait of decentralized application users: an overview based on large-scale Ethereum data. CCF Transactions on Pervasive Computing and Interaction, 4(2), 124-141. Min T. Cai W. ( 2022 ). Portrait of decentralized application users: an overview based on large-scale Ethereum data . CCF Transactions on Pervasive Computing and Interaction , 4 ( 2 ), 124 - 141 . Search in Google Scholar

[13] Korolev, V. Y., Korchagin, A. Y., Mashechkin, I. V., Petrovskii, M. I., & Tsarev, D. V. (2018). Applying Time Series for Background User Identification Based on Their Text Data Analysis. Programming and Computer Software, 44, 353-362. Korolev V. Y. Korchagin A. Y. Mashechkin I. V. Petrovskii M. I. Tsarev D. V. ( 2018 ). Applying Time Series for Background User Identification Based on Their Text Data Analysis . Programming and Computer Software , 44 , 353 - 362 . Search in Google Scholar

[14] Chen, C., Yan, J., Wang, L., Liang, D., & Zhang, W. (2020). Classification of urban functional areas from remote sensing images and time-series user behavior data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 1207-1221. Chen C. Yan J. Wang L. Liang D. Zhang W. ( 2020 ). Classification of urban functional areas from remote sensing images and time-series user behavior data . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 14 , 1207 - 1221 . Search in Google Scholar

[15] Athiyarath, S., Paul, M., & Krishnaswamy, S. (2020). A comparative study and analysis of time series forecasting techniques. SN Computer Science, 1(3), 175. Athiyarath S. Paul M. Krishnaswamy S. ( 2020 ). A comparative study and analysis of time series forecasting techniques . SN Computer Science , 1 ( 3 ), 175 . Search in Google Scholar

[16] Lim, B., & Zohren, S. (2021). Time-series forecasting with deep learning: a survey. Philosophical Transactions of the Royal Society A, 379(2194), 20200209. Lim B. Zohren S. ( 2021 ). Time-series forecasting with deep learning: a survey . Philosophical Transactions of the Royal Society A , 379 ( 2194 ), 20200209 . Search in Google Scholar

[17] Du, Y., Wang, J., Feng, W., Pan, S., Qin, T., Xu, R., & Wang, C. (2021, October). Adarnn: Adaptive learning and forecasting of time series. In Proceedings of the 30th ACM international conference on information & knowledge management (pp. 402-411). Du Y. Wang J. Feng W. Pan S. Qin T. Xu R. Wang C. ( 2021 , October ). Adarnn: Adaptive learning and forecasting of time series . In Proceedings of the 30th ACM international conference on information & knowledge management (pp. 402 - 411 ). Search in Google Scholar

[18] Yang, Z., Yan, W., Huang, X., & Mei, L. (2020). Adaptive temporal-frequency network for time-series forecasting. IEEE Transactions on Knowledge and Data Engineering, 34(4), 1576-1587. Yang Z. Yan W. Huang X. Mei L. ( 2020 ). Adaptive temporal-frequency network for time-series forecasting . IEEE Transactions on Knowledge and Data Engineering , 34 ( 4 ), 1576 - 1587 . Search in Google Scholar

[19] Dibrivnyi, О. А. (2018). Comparative analysis of time series forecasting based on the trend model and adaptive browns model. Телекомунікаційні та інформаційні технології, (1), 88-95. Dibrivnyi О. А. ( 2018 ). Comparative analysis of time series forecasting based on the trend model and adaptive browns model . Телекомунікаційні та інформаційні технології , ( 1 ), 88 - 95 . Search in Google Scholar

[20] Wang, Y., & Han, L. (2021). Adaptive time series prediction and recommendation. Information Processing & Management, 58(3), 102494. Wang Y. Han L. ( 2021 ). Adaptive time series prediction and recommendation . Information Processing & Management , 58 ( 3 ), 102494 . Search in Google Scholar

[21] Masoud Golalikhani,Beatriz Brito Oliveira,Gonçalo Homem de Almeida Correia,José Fernando Oliveira & Maria Antónia Carravilla. (2024). Optimizing multi-attribute pricing plans with time- and location-dependent rates for different carsharing user profiles. Transportation Research Part E103760-103760. Golalikhani Masoud Oliveira Beatriz Brito Correia Gonçalo Homem de Almeida Oliveira José Fernando Carravilla Maria Antónia ( 2024 ). Optimizing multi-attribute pricing plans with time- and location-dependent rates for different carsharing user profiles . Transportation Research Part E 103760 - 103760 . Search in Google Scholar

[22] Wei han Liu & Xingfu Xu. (2024). Forecasting crude oil price: A deep forest ensemble approach. Finance Research Letters(PB),106153-106153. Liu Wei han Xu Xingfu ( 2024 ). Forecasting crude oil price: A deep forest ensemble approach . Finance Research Letters(PB) , 106153 - 106153 . Search in Google Scholar

[23] Da Liu,Yanan Wei,Shuxia Yang & Zhitao Guan. (2013). Electricity Price Forecast Using Combined Models with Adaptive Weights Selected and Errors Calibrated by Hidden Markov Model. Mathematical Problems in Engineering1-8. Liu Da Wei Yanan Yang Shuxia Guan Zhitao ( 2013 ). Electricity Price Forecast Using Combined Models with Adaptive Weights Selected and Errors Calibrated by Hidden Markov Model . Mathematical Problems in Engineering 1 - 8 . Search in Google Scholar