TWILITE: A recommendation system for Twitter using a probabilistic model based on latent Dirichlet allocation
We propose a probabilistic model by generalizing LDA to capture the behaviors of users in Twitter. A variational EM algorithm is presented for our model. We develop recommendation algorithms using the parameters estimated by the inference algorithm. We did performance study to show the effectiveness of our model and recommendation algorithms. Our recommendation algorithms are much more accurate than traditional algorithms in experiments.
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