Results 1 to 10 of about 23,536,819 (378)
Topic Modeling in Embedding Spaces [PDF]
Transactions of the Association for Computational Linguistics, 2020 Topic modeling analyzes documents to learn meaningful patterns of words. However, existing topic models fail to learn interpretable topics when working with large and heavy-tailed vocabularies.
Dieng, Adji B. +2 more
doaj +6 more sources
BERTopic: Neural topic modeling with a class-based TF-IDF procedure [PDF]
arXiv, 2022 Topic models can be useful tools to discover latent topics in collections of documents. Recent studies have shown the feasibility of approach topic modeling as a clustering task. We present BERTopic, a topic model that extends this process by extracting coherent topic representation through the development of a class-based variation of TF-IDF.
M. Grootendorst
arxiv +3 more sources
Crime Science, 2017 The classification of crime into discrete categories entails a massive loss of information. Crimes emerge out of a complex mix of behaviors and situations, yet most of these details cannot be captured by singular crime type labels.
Da Kuang +2 more
doaj +7 more sources
Topic Modeling for Analyzing Topic Manipulation Skills [PDF]
Information, 2021 There are many ways to communicate with people, the most representative of which is a conversation. A smooth conversation should not only be written in a grammatically appropriate manner, but also deal with the subject of conversation; this is known as ...
Seok-Ju Hwang +4 more
doaj +2 more sources
Efficient Correlated Topic Modeling with Topic Embedding [PDF]
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2017 Correlated topic modeling has been limited to small model and problem sizes due to their high computational cost and poor scaling. In this paper, we propose a new model which learns compact topic embeddings and captures topic correlations through the ...
Berg-Kirkpatrick, Taylor +4 more
core +3 more sources
Combined models for topic spotting and topic-dependent language modeling [PDF]
1997 IEEE Workshop on Automatic Speech Recognition and Understanding Proceedings, 2002 A new statistical method for Language Modeling and spoken document classification is proposed. It is based on a mixture of topic dependent probabilities. Each topic dependent probability is in turn a mixture of n-gram probabilities and the probability of Kullback-Lieber (KL) distances between keyword unigrams and distribution obtained from the content ...
Brigitte Bigi +3 more
openalex +5 more sources
LDA-Based Topic Modeling Sentiment Analysis Using Topic/Document/Sentence (TDS) Model
Applied Sciences, 2021 Customer reviews on the Internet reflect users’ sentiments about the product, service, and social events. As sentiments can be divided into positive, negative, and neutral forms, sentiment analysis processes identify the polarity of information in the ...
Akhmedov Farkhod +3 more
doaj +2 more sources
Polylingual topic models [PDF]
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing Volume 2 - EMNLP '09, 2009 Topic models are a useful tool for analyzing large text collections, but have previously been applied in only monolingual, or at most bilingual, contexts. Meanwhile, massive collections of interlinked documents in dozens of languages, such as Wikipedia, are now widely available, calling for tools that can characterize content in many languages.
David Mimno +4 more
openalex +3 more sources
Topic selection for text classification using ensemble topic modeling with grouping, scoring, and modeling approach [PDF]
Scientific ReportsTextNetTopics (Yousef et al. in Front Genet 13:893378, 2022. https://doi.org/10.3389/fgene.2022.893378 ) is a recently developed approach that performs text classification-based topics (a topic is a group of terms or words) extracted from a Latent ...
Daniel Voskergian +2 more
doaj +2 more sources