We propose a simple strategy to learn incrementally the latent factors at each time step. Our method takes only recent data to update latent factor models and ...
We propose a simple strategy to learn incrementally the latent factors at each time step. Our method takes only recent data to update latent factor models and ...
PDF | In this paper, we focus on the problem of predicting some particular user activities in social media. Our challenge is to consider real events.
Aug 19, 2015 · Abstract. In this paper, we focus on the problem of predicting some particular user activities in social media. Our challenge is to consider.
Abstract. In this paper, we focus on the problem of predicting some particular user activities in social media. Our challenge is to consider real events ...
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This information fusion from historical data allows both the real-time prediction and the online incremental learning to adapt the model to new incoming ...
Because. NED techniques involve continuous monitoring of Twitter data for discovering new events in near real time, they are naturally suited for detecting ...
Online Incremental Machine Learning Platform for Big Data-Driven Smart ...
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The STMP integrates the heterogeneous big data streams, such as the IoT, smart sensors, and social media, to detect concept drifts, distinguish between the ...
Real-time workflow for incrementally learning a classifier for new events when they arise. 2.2. Near-real-time incremental learning. The proposed workflow ...
Online machine learning is an approach that feeds data to the machine learning model in an incremental manner, which can leverage continuous streams.