  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.
