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Conference Papers Year : 2020

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

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.

Dates and versions

hal-03554622 , version 1 (03-02-2022)

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Cite

Pasquale Lisena, Ismail Harrando, Oussama Kandakji, Raphaël Troncy. TOMODAPI: A Topic Modeling API to Train, Use and Compare Topic Models. NLP-OSS 2020, Proceedings of Second Workshop for NLP Open Source Software, Nov 2020, Online, France. pp.132-140, ⟨10.18653/v1/2020.nlposs-1.19⟩. ⟨hal-03554622⟩

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