STTM: A Tool for Short Text Topic Modeling

August 07, 2018 ยท Entered Twilight ยท ๐Ÿ› arXiv.org

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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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