The LSTM model presented is capable of describing a user of a particular website without human expert supervision. In other words, the model is able to automatically craft features which depict attitude, intention and the overall state of a user.
Feb 12, 2017
The LSTM model was used to produce user2vec which projects history of an individual user into a fixed-size vector which may be treated as a set of new features ...
User Modeling Using LSTM Networks · Konrad Zolna, B. Romanski · Published in AAAI Conference on Artificial… 12 February 2017 · Computer Science.
The LSTM model presented is capable of describing a user of a particular website without human expert supervision. In other words, the model is able to ...
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Actions' time intervals are modeled by time gates in Time-LSTM to capture actions' relations.
Jun 25, 2016 · The LSTM model presented is capable of describing a user of a particular website without human expert supervision. In other words, the model is ...
Jan 28, 2020 · You can forecast using spatio-temporal data by combining Graph Convolution Networks with LSTM models! The idea comes from a paper by Zhao et al.
LSTM has many advantages over other feedforward and recurrent NNs in modeling of time series, such as audio and video.
This example shows how to create a reduced order model (ROM) to replace a Simscape component in a Simulink® model by training a long short-term memory (LSTM) ...
In this paper, we introduce Latent LSTM Allocation (LLA) for user modeling combining hierarchical Bayesian models with LSTMs.