18 skills found
MilaNLProc / Contextualized Topic ModelsA python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021 (Bianchi et al.).
dice-group / PalmettoPalmetto is a quality measuring tool for topics
fozziethebeat / TopicModelComparisonScripts and codes for replicating experiments published in Exploring Topic Coherence over many models and many topics
lxing532 / Dialogue Topic SegmenterImproving Unsupervised Dialogue Topic Segmentation with Utterance-Pair Coherence Scoring
jhlau / Topic Coherence SensitivityCode to compute topic coherence for several topic cardinalities and aggregate scores across them
IkshitaMishra / TopicModelling LSA LDARetrieving 'Topics' (concept) from corpus using (1) Latent Dirichlet Allocation (Genism) for modelling. Perplexity and Coherence score were used as evaluation models. (2) Latent Semantic Analysis using Term Frequency- Inverse Document Frequency and Truncated Singular Value Decomposition.
kelvinlo-uni / Transformer SquaredTransformer over Pre-trained Transformer for Neural Text Segmentation with Enhanced Topic Coherence
davidandrzej / SemcoCalculate latent topic semantic coherence (Mimno et al, EMNLP 2011)
hamedR96 / CTCContextualised Topic Coherence Metrics: A new way to evaluate neural topic models.
suhasmaddali / English Language Learning Prediction With AI And Machine LearningArtificial intelligence is being used to improve essay writing skills by evaluating student essays. NLP techniques analyze coherence, clarity, and relevance, while topic modeling and sentiment analysis determine main themes and emotional tone. Machine learning algorithms evaluate essays and provide feedback to help students improve their writing.
raymondzmc / Topic Model Diversity Aware Coherence LossNo description available
Renata1995 / Topic Distance And CoherenceCodes to analyze distance and coherence of topics generated by LDA
dkorenci / Doc Topic CoherenceCode of the experiments from the article "Document-based Topic Coherence Measures for News Media Text"
datquocnguyen / MAP4LDAImproving Topic Coherence with Latent Feature Word Representations in MAP Estimation for Topic Modeling (ALTA 2015)
bharathbolla / Topic Modeling Using Bert EmbeddingsCustomers' reviews and comments are important for businesses to understand users' sentiment about the products and services. However, this data needs to be analyzed to assess the sentiment associated with topics/aspects to provide efficient customer assistance. LDA and LSA fail to capture the semantic relationship and are not specific to any domain. In this study, we evaluate BERTopic, a novel method that generates topics using sentence embeddings on Consumer Financial Protection Bureau (CFPB) data. Our work shows that BERTopic is flexible and yet provides meaningful and diverse topics compared to LDA and LSA. Furthermore, domain-specific pre-trained embeddings (FinBERT) yield even better topics. We evaluated the topics on coherence score (c_v) and UMass.
Fatema29 / Topic Modeling And Text ClassificationAn analysis was made into a text dataset which contains short text and by comparing different methods to find the best model. For the text classification problem Naive Bayes, Regression Analysis, CNN in supervised method was implemented. For the topic modeling problem, I implemented LDA and NMF method to observe the performances and measured the performance by comparing the coherence value.
Sadykhzadeh / YBalaBot🫰🏻I will continue your text on any topic, preserving coherence and the desired style.
NeverForged / LDATopicCoherenceBuilding a scorer for grid searches based on topic coherence for use with sklearn's LDA model.
