most citedTwitter-Network Topic Model: A Full Bayesian Treatment for Social Network and Text Modeling

44 citations · 175 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG201618 cited

Hawkes Processes with Stochastic Excitations

Young Lee, Kar Wai Lim, Cheng Soon Ong

We propose an extension to Hawkes processes by treating the levels of self-excitation as a stochastic differential equation. Our new point process allows better approximation in ap…

cs.DL201632 cited

Bibliographic Analysis with the Citation Network Topic Model

Kar Wai Lim, Wray Buntine

Bibliographic analysis considers author's research areas, the citation network and paper content among other things. In this paper, we combine these three in a topic model that pro…

cs.CL201644 cited

Twitter-Network Topic Model: A Full Bayesian Treatment for Social Network and Text Modeling

Kar Wai Lim, Changyou Chen, Wray Buntine

Twitter data is extremely noisy -- each tweet is short, unstructured and with informal language, a challenge for current topic modeling. On the other hand, tweets are accompanied b…

stat.ML201637 cited

Nonparametric Bayesian Topic Modelling with the Hierarchical Pitman-Yor Processes

Kar Wai Lim, Wray Buntine, Changyou Chen +1

The Dirichlet process and its extension, the Pitman-Yor process, are stochastic processes that take probability distributions as a parameter. These processes can be stacked up to f…

cs.CL201644 cited

Twitter Opinion Topic Model: Extracting Product Opinions from Tweets by Leveraging Hashtags and Sentiment Lexicon

Kar Wai Lim, Wray Buntine

Aspect-based opinion mining is widely applied to review data to aggregate or summarize opinions of a product, and the current state-of-the-art is achieved with Latent Dirichlet All…