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Cited by 2,152

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Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

Open access
Lai, Guokun, Chang, Wei-Cheng, Yang, Yiming, Liu, Hanxiao·2018·The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval
DOI 10.1145/3209978.3210006
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Abstract

Multivariate time series forecasting is an important machine learning problem across many domains, including predictions of solar plant energy output, electricity consumption, and traffic jam situation. Temporal data arise in these real-world applications often involves a mixture of long-term and short-term patterns, for which traditional approaches such as Autoregressive models and Gaussian Process may fail. In this paper, we proposed a novel deep learning framework, namely Long- and Short-term Time-series network (LSTNet), to address this open challenge. LSTNet uses the Convolution Neural Network (CNN) and the Recurrent Neural Network (RNN) to extract short-term local dependency patterns among variables and to discover long-term patterns for time series trends. Furthermore, we leverage traditional autoregressive model to tackle the scale insensitive problem of the neural network model. In our evaluation on real-world data with complex mixtures of repetitive patterns, LSTNet achieved significant performance improvements over that of several state-of-the-art baseline methods. All the data and experiment codes are available online.

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Metadata

Authors
Lai, G., Chang, W.-C., Yang, Y., & Liu, H.
Venue
The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval
Publisher
ACM
Published
2018-06-27
Pages
95-104
DOI
10.1145/3209978.3210006
OpenAlex
W2604847698
Cited by
2,152
References
4
FWCI
78.99
Type
conference paper
Language
en
Open access
green
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)

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CoChat. (2026). Citation check: Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks. https://app.cochat.ai/papers/10.1145/3209978.3210006
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Lai, G., Chang, W.-C., Yang, Y., & Liu, H. (2018). Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks. The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval. https://doi.org/10.1145/3209978.3210006

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