الملخص
Media-bridged time series forecasting is expanding to encompass traditional "multivariate" and emerging "multimodal" (e.g., through textual assistance). Existing Time Series Forecasting (TSF) models still rely on paradigm-specific relation, fusion, and temporal modules, hindering a common forecasting backbone across numerical and pre-aligned narrative-flow settings. To explore this, we propose the Multimedia Identity-Aware Prism Network (MIDAPN), a unified spatiotemporal forecasting backbone based on media-general graph adaptation and automatic temporal learning: (1) Following media pre-alignment, our Multimedia Identity-Aware Graph (MIDAG) revisits identity through static essence, dynamic behavior, and latent commonality, inducing affinities that extend variable-specific dependencies across media. Contextual Identity Modulation (CIM) further refines discriminative aggregation. (2) We develop Spectral Prism Convolution (SPConv) to automatically perform hierarchical temporal analysis, balancing coarse trends and fine-grained details. Meanwhile, its Adaptive Search Guidance configures a scale-efficient architecture for temporal-dimension reconstruction. These decoupled yet synergistic components jointly address media identity disentanglement and temporal-scale mismatch. Comprehensive evaluations involving 16 SOTA TSF models across 13 "multivariate" and 12 "multimodal" datasets, alongside targeted long-context comparisons against 14 time series foundation models and fused pretrained language models, demonstrate MIDAPN's consistent superiority and broad shared backbone compatibility. The code is available at \href{https://github.com/leijieruilq/MIDAPN/tree/main}{https://github.com/MIDAPN}.
الكلمات المفتاحية
الموضوع
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Lei, J., Zhang, W., Yang, Q., Hong, Y., Chen, F., Zhang, Z., Tang, H., & Xiang, S. (2026). Revisiting Identity and Spectra Dispersion in Media-Bridged Time Series Forecasting: Linking Multivariate Signals and Narrative Flows. https://omanscience.com/ar/articles/revisiting-identity-and-spectra-dispersion-in-media-bridged-time-series-forecasting-linking-multivariate-signals-and-narrative-flows
MLA 9
Lei, Jierui, et al. "Revisiting Identity and Spectra Dispersion in Media-Bridged Time Series Forecasting: Linking Multivariate Signals and Narrative Flows." https://omanscience.com/ar/articles/revisiting-identity-and-spectra-dispersion-in-media-bridged-time-series-forecasting-linking-multivariate-signals-and-narrative-flows.
شيكاغو (المؤلف–التاريخ)
Lei, Jierui, Wenjian Zhang, Qingyi Yang, Yuyang Hong, Fangzheng Chen, Zhengbo Zhang, Haina Tang, and Shiming Xiang. 2026. "Revisiting Identity and Spectra Dispersion in Media-Bridged Time Series Forecasting: Linking Multivariate Signals and Narrative Flows." https://omanscience.com/ar/articles/revisiting-identity-and-spectra-dispersion-in-media-bridged-time-series-forecasting-linking-multivariate-signals-and-narrative-flows.
هارفارد
Lei, J., Zhang, W., Yang, Q., Hong, Y., Chen, F., Zhang, Z., Tang, H. and Xiang, S. (2026) 'Revisiting Identity and Spectra Dispersion in Media-Bridged Time Series Forecasting: Linking Multivariate Signals and Narrative Flows', Available at: https://omanscience.com/ar/articles/revisiting-identity-and-spectra-dispersion-in-media-bridged-time-series-forecasting-linking-multivariate-signals-and-narrative-flows.
فانكوفر
Lei J, Zhang W, Yang Q, Hong Y, Chen F, Zhang Z, et al. Revisiting Identity and Spectra Dispersion in Media-Bridged Time Series Forecasting: Linking Multivariate Signals and Narrative Flows. https://omanscience.com/ar/articles/revisiting-identity-and-spectra-dispersion-in-media-bridged-time-series-forecasting-linking-multivariate-signals-and-narrative-flows
IEEE
J. Lei, W. Zhang, Q. Yang, Y. Hong, F. Chen, Z. Zhang, H. Tang, and S. Xiang, "Revisiting Identity and Spectra Dispersion in Media-Bridged Time Series Forecasting: Linking Multivariate Signals and Narrative Flows," https://omanscience.com/ar/articles/revisiting-identity-and-spectra-dispersion-in-media-bridged-time-series-forecasting-linking-multivariate-signals-and-narrative-flows.