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STTM: A Tool for Short Text Topic Modeling
August 07, 2018 ยท Entered Twilight ยท ๐ arXiv.org
"Last commit was 6.0 years ago (โฅ5 year threshold)"
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Repo contents: Architecture.png, README.md, dataset, jar, lib, process_wiki.py, run.sh, src
Authors
Jipeng Qiang, Yun Li, Yunhao Yuan, Wei Liu, Xindong Wu
arXiv ID
1808.02215
Category
cs.IR: Information Retrieval
Citations
16
Venue
arXiv.org
Repository
https://github.com/qiang2100/STTM
โญ 160
Last Checked
1 month ago
Abstract
Along with the emergence and popularity of social communications on the Internet, topic discovery from short texts becomes fundamental to many applications that require semantic understanding of textual content. As a rising research field, short text topic modeling presents a new and complementary algorithmic methodology to supplement regular text topic modeling, especially targets to limited word co-occurrence information in short texts. This paper presents the first comprehensive open-source package, called STTM, for use in Java that integrates the state-of-the-art models of short text topic modeling algorithms, benchmark datasets, and abundant functions for model inference and evaluation. The package is designed to facilitate the expansion of new methods in this research field and make evaluations between the new approaches and existing ones accessible. STTM is open-sourced at https://github.com/qiang2100/STTM.
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