Topic Models

141 papers with code • 3 benchmarks • 5 datasets

A topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for the discovery of hidden semantic structures in a text body.

Greatest papers with code

Software Framework for Topic Modelling with Large Corpora

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

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

cemoody/lda2vec 6 May 2016

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.

Document-level Topic Models +1

Familia: A Configurable Topic Modeling Framework for Industrial Text Engineering

baidu/Familia 11 Aug 2018

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

Familia: An Open-Source Toolkit for Industrial Topic Modeling

baidu/Familia 31 Jul 2017

Familia is an open-source toolkit for pragmatic topic modeling in industry.

Model Selection Topic Models

Top2Vec: Distributed Representations of Topics

ddangelov/Top2Vec 19 Aug 2020

Distributed representations of documents and words have gained popularity due to their ability to capture semantics of words and documents.

Lemmatization Semantic Similarity +2

Neural Variational Inference for Text Processing

carpedm20/variational-text-tensorflow 19 Nov 2015

We validate this framework on two very different text modelling applications, generative document modelling and supervised question answering.

Answer Selection Latent Variable Models +2

Cross-lingual Contextualized Topic Models with Zero-shot Learning

MilaNLProc/contextualized-topic-models EACL 2021

They all cover the same content, but the linguistic differences make it impossible to use traditional, bag-of-word-based topic models.

Topic Models Transfer Learning +2

Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherence

MilaNLProc/contextualized-topic-models 8 Apr 2020

Topic models extract groups of words from documents, whose interpretation as a topic hopefully allows for a better understanding of the data.

Sentence Embeddings Topic Models +1

Topic Modeling in Embedding Spaces

adjidieng/ETM TACL 2020

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 Variational Inference +1

An Unsupervised Neural Attention Model for Aspect Extraction

ruidan/Unsupervised-Aspect-Extraction ACL 2017

Unlike topic models which typically assume independently generated words, word embedding models encourage words that appear in similar contexts to be located close to each other in the embedding space.

Aspect Extraction Domain Adaptation +2