Cited By
View all- Amur ZKwang Hooi YBhanbhro HDahri KSoomro G(2023)Short-Text Semantic Similarity (STSS): Techniques, Challenges and Future PerspectivesApplied Sciences10.3390/app1306391113:6(3911)Online publication date: 19-Mar-2023
Short Text Clustering in Continuous Time Using Stacked Dirichlet-Hawkes Process with Inverse Cluster Frequency Prior
Pages 118 - 122
Abstract
Traditional models for short text clustering ignore the time information associated with the text documents. However, existing works have shown that temporal characteristics of streaming documents are significant features for clustering. In this paper we propose a stacked Dirichlet-Hawkes process with inverse cluster frequency prior as a simple but effective solution for the task of short text clustering using temporal features in continuous time. Based on the classical formulation of the Dirichlet-Hawkes process, our model provides an elegant, theoretically grounded and interpretable solution while performing at par with recent state of the art models in short text clustering.
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- Short Text Clustering in Continuous Time Using Stacked Dirichlet-Hawkes Process with Inverse Cluster Frequency Prior
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January 2023
357 pages
ISBN:9781450397971
DOI:10.1145/3570991
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Published: 04 January 2023
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CODS-COMAD 2023
CODS-COMAD 2023: 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD)
January 4 - 7, 2023
Mumbai, India
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View all- Amur ZKwang Hooi YBhanbhro HDahri KSoomro G(2023)Short-Text Semantic Similarity (STSS): Techniques, Challenges and Future PerspectivesApplied Sciences10.3390/app1306391113:6(3911)Online publication date: 19-Mar-2023
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