Software Framework for Topic Modelling with Large Corpora

Workshop On New Challenges For NLP Frameworks 2010 • RaRe-Technologies/gensim

Large corpora are ubiquitous in today’s world and memory quickly becomes the limiting factor in practical applications of the Vector Space Model (VSM).

TOPIC MODELS

Mixing Dirichlet Topic Models and Word Embeddings to Make lda2vec

6 May 2016 • cemoody/lda2vec

Distributed dense word vectors have been shown to be effective at capturing token-level semantic and syntactic regularities in language, while topic models can form interpretable representations over documents.

TOPIC MODELS WORD EMBEDDINGS

Familia: A Configurable Topic Modeling Framework for Industrial Text Engineering

11 Aug 2018 • baidu/Familia

In order to relieve burdens of software engineers without knowledge of Bayesian networks, Familia is able to conduct automatic parameter inference for a variety of topic models.

TOPIC MODELS

Generative Topic Embedding: a Continuous Representation of Documents

ACL 2016 • askerlee/topicvec

DOCUMENT CLASSIFICATION TOPIC MODELS

Autoencoding Variational Inference For Topic Models

4 Mar 2017 • akashgit/autoencoding_vi_for_topic_models •

A promising approach to address this problem is autoencoding variational Bayes (AEVB), but it has proven diffi- cult to apply to topic models in practice.

TOPIC MODELS

Computing Web-scale Topic Models using an Asynchronous Parameter Server

24 May 2016 • rjagerman/glint

Topic models such as Latent Dirichlet Allocation (LDA) have been widely used in information retrieval for tasks ranging from smoothing and feedback methods to tools for exploratory search and discovery.

INFORMATION RETRIEVAL TOPIC MODELS

Topic Modeling in Embedding Spaces

8 Jul 2019 • adjidieng/ETM •

To this end, we develop the Embedded Topic Model (ETM), a generative model of documents that marries traditional topic models with word embeddings.

TOPIC MODELS WORD EMBEDDINGS

Machine Reading Tea Leaves: Automatically Evaluating Topic Coherence and Topic Model Quality

EACL 2014 • jhlau/topic_interpretability

MACHINE TRANSLATION READING COMPREHENSION TOPIC MODELS

Gaussian LDA for Topic Models with Word Embeddings

IJCNLP 2015 • rajarshd/Gaussian_LDA

TOPIC MODELS WORD EMBEDDINGS

A Scalable Asynchronous Distributed Algorithm for Topic Modeling

16 Dec 2014 • dmlc/experimental-lda

Learning meaningful topic models with massive document collections which contain millions of documents and billions of tokens is challenging because of two reasons: First, one needs to deal with a large number of topics (typically in the order of thousands).

TOPIC MODELS