CFMf topic-model: comparison with LDA and Top2Vec
Mining the content of scientific publications is increasingly used to investigate the practice of
science and the evolution of research domains. Topic models, among which LDA (statistical …
science and the evolution of research domains. Topic models, among which LDA (statistical …
Regularized semi-supervised KLFDA algorithm based on density peak clustering
To solve the problem that the existing semi-supervised FISHER discriminant analysis
algorithm (FDA) cannot effectively use both labeled and unlabeled data for learning, we …
algorithm (FDA) cannot effectively use both labeled and unlabeled data for learning, we …
Apache Spark-based scalable feature extraction approaches for protein sequence and their clustering performance analysis
Genome sequencing projects are rapidly contributing to the rise of high-dimensional protein
sequence datasets. Extracting features from a high-dimensional protein sequence dataset …
sequence datasets. Extracting features from a high-dimensional protein sequence dataset …
Enhancing LDA Method by the Use of Feature Maximization
Topic modeling is a key technique for understanding the content of collections of scientific
papers. However, commonly used methods like LDA (Latent Dirichlet Allocation) have …
papers. However, commonly used methods like LDA (Latent Dirichlet Allocation) have …
Enhancing LDA Method by the Use
Topic modeling is a key technique for understanding the con-tent of collections of scientific
papers. However, commonly used methods like LDA (Latent Dirichlet Allocation) have …
papers. However, commonly used methods like LDA (Latent Dirichlet Allocation) have …
Neural Networks for Spatial Models
The aim of spatial econometrics is to analyze and/or predict the relationship between one
dependent variable Y with other variables, building a model that takes into account the …
dependent variable Y with other variables, building a model that takes into account the …
[PDF][PDF] Analyse non supervisée de corpus de documents pour la recherche de sujets: une nouvelle approche basée sur le clustering et la maximisation des traits
Le présent article s' intéresse à l'extraction non supervisée des sujets portés par les
collections de documents qui est un thème du front de recherche. Il présente une nouvelle …
collections de documents qui est un thème du front de recherche. Il présente une nouvelle …
[PDF][PDF] La méthode de modélisation thématique CFMf basée sur le clustering neuronal avec maximisation des traits: Comparaison avec LDA sur des études …
Résumé L'amélioration des méthodes de modélisation thématique reste une préoccupation
majeure pour l'analyse non supervisée des données textuelles. Nous proposons ici une …
majeure pour l'analyse non supervisée des données textuelles. Nous proposons ici une …