Familia: An Open-Source Toolkit for Industrial Topic Modeling

July 31, 2017 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Di Jiang, Zeyu Chen, Rongzhong Lian, Siqi Bao, Chen Li arXiv ID 1707.09823 Category cs.IR: Information Retrieval Cross-listed cs.CL Citations 1 Venue arXiv.org Last Checked 4 months ago
Abstract
Familia is an open-source toolkit for pragmatic topic modeling in industry. Familia abstracts the utilities of topic modeling in industry as two paradigms: semantic representation and semantic matching. Efficient implementations of the two paradigms are made publicly available for the first time. Furthermore, we provide off-the-shelf topic models trained on large-scale industrial corpora, including Latent Dirichlet Allocation (LDA), SentenceLDA and Topical Word Embedding (TWE). We further describe typical applications which are successfully powered by topic modeling, in order to ease the confusions and difficulties of software engineers during topic model selection and utilization.
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