Papers by Guanfeng Liu

1 papers
Leveraging Meta Information in Short Text Aggregation (P19-1)

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Challenge: Existing topic models infer topics based on word co-occurrence information, which results in degraded performance and degrades performance.
Approach: They propose a generative model that aggregates short texts into clusters by leveraging the associated meta information.
Outcome: The proposed model can generate more interpretable topics and document clusters.

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