STTM swMATH ID: 28482 Software Authors: Jipeng Qiang, Yun Li, Yunhao Yuan, Wei Liu, Xindong Wu Description: STTM: A Tool for Short Text Topic Modeling. 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 Homepage: https://arxiv.org/abs/1808.02215 Source Code: https://github.com/qiang2100/STTM Keywords: Information Retrieval; arXiv_cs.IR; Topic Modeling; Short Text; LDA; Java Related Software: Cited in: 0 Documents Standard Articles 1 Publication describing the Software Year STTM: A Tool for Short Text Topic Modeling arXiv Jipeng Qiang, Yun Li, Yunhao Yuan, Wei Liu, Xindong Wu 2018