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TOMODAPI: A Topic Modeling API to Train, Use and Compare Topic Models

2020-11-01EMNLP (NLPOSS) 2020Code Available1· sign in to hype

Pasquale Lisena, Ismail Harrando, Oussama Kandakji, Raphael Troncy

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Abstract

From LDA to neural models, different topic modeling approaches have been proposed in the literature. However, their suitability and performance is not easy to compare, particularly when the algorithms are being used in the wild on heterogeneous datasets. In this paper, we introduce ToModAPI (TOpic MOdeling API), a wrapper library to easily train, evaluate and infer using different topic modeling algorithms through a unified interface. The library is extensible and can be used in Python environments or through a Web API.

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