latent-semantic-analysis
There are 4 repositories under latent-semantic-analysis topic.
- OCTIS
MIND-Lab / OCTIS
OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)
Language:Python 688 james-bowman / nlp
Selected Machine Learning algorithms for natural language processing and semantic analysis in Golang
Language:Go 432- machine-learning
je-suis-tm / machine-learning
Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, NaĂŻve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression
naive-bayessupport-vector-machinestochastic-gradient-descentbatch-gradient-descentnewton-methodmultinomial-naive-bayeslinear-discriminant-analysissequential-minimal-optimizationk-nearest-neighborsdbscanexpectation-maximizationexpectation-maximization-algorithmfactor-analysisindependent-component-analysislatent-semantic-analysislow-rank-approximationsingular-value-decompositionridge-regressionlasso-regressionem-algorithmLanguage:Jupyter Notebook 206 josephwilk / rsemantic
A document vector search with flexible matrix transforms. Currently supports Latent semantic analysis and Term frequency - inverse document frequency
Language:Ruby 147tra38 / ZombieWriter
ZombieWriter is a Ruby gem that will enable users to generate news articles by aggregating paragraphs from other sources.
Language:Ruby 76jonaschn / awesome-topic-models
✨ Awesome - A curated list of amazing Topic Models (implementations, libraries, and resources)
awesometopic-modelingawesome-listtopic-modelstopic-modelnlptext-mininglatent-dirichlet-allocationlatent-semantic-analysistruncated-svdnon-negative-matrix-factorizationhierarchical-dirichlet-processesdynamic-topic-modelingauthor-topic-modellabeled-ldadirichlet-multinomialdirichlet-process-mixturessentence-ldamattmurray / topic_modelling_financial_news
Topic modelling on financial news with Natural Language Processing
Language:Jupyter Notebook 56aliprf / GANalyzer
GANalyzer: Analysis and Manipulation of GANs Latent Space for Controllable Face Synthesis
Language:Python 29dayyass / latent-semantic-analysis
Pipeline for training LSA models using Scikit-Learn.
Language:Python 23- Language:Python 18
zgornel / StringAnalysis.jl
Hard-Forked from JuliaText/TextAnalysis.jl
Language:Julia 17KingJamesSong / HouseholderGAN
ICCV23 "Householder Projector for Unsupervised Latent Semantics Discovery"
Language:Python 16sudharsan13296 / Document-Classification-using-LSA
Document classification using Latent semantic analysis in python
Language:Jupyter Notebook 16a-paxton / Gensim-LSI-Word-Similarities
Generate word-word similarities from Gensim's latent semantic indexing (Python)
Language:Python 11- Language:C 10
moj-analytical-services / pq-tool
Tool to analyse past parliamentary questions with visualisation in RShiny
Language:R 10- Language:Java 10
abhi40308 / News-Documents-Clustering
News documents clustering using latent semantic analysis
Language:Jupyter Notebook 7RP-72 / Latent-Semantic-Indexing-from-scratch
Information retrieval and text mining using SVD in LSI. SVD has been implemented completely from scratch.
Language:Python 7Tuhin-SnapD / Text-Summarization-Models
This repository contains various models for text summarization tasks. Each model has a separate directory containing the implementation code, pretrained weights, and a Jupyter notebook for testing the model on sample input texts. Feel free to use these models for your own text summarization tasks or to experiment with them further.
Language:Jupyter Notebook 7ZirvedaAytimur / Natural-Language-Processing-NLP-
The examples I prepared and brought together about the natural language processing topics I learned.
Language:Jupyter Notebook 7fahd09 / neurosynth_semantic_map
A repository for "The Latent Semantic Space and Corresponding Brain Regions of the Functional Neuroimaging Literature" -- http://www.biorxiv.org/content/early/2017/07/20/157826
Language:R 6- reddit-tldr-summarizer-and-topic-modeling
giocoal / reddit-tldr-summarizer-and-topic-modeling
Extreme Extractive Text Summarization and Topic Modeling (using LSA and LDA techniques) over Reddit Posts from TLDRHQ dataset.
Language:Python 6 ArupDas15 / Anwesha
The work presents “Anwesha: A tool for Semantic Search in Bangla”. This work shows explorations toward building a search engine prototype in Bangla language. The work used sources from WordNet, Wikipedia and statistical co-occurences(LSA) for retrieval of semantically related documents.
Language:Python 5harishaaram / Topic-Modeling
An Unbiased Examination of Federal Reserve Meeting minutes
Language:Jupyter Notebook 5melodiCyb / natural-language-processing
LSA, Viterbi, word2vec, SVM, Naive Bayes
kaustubhbhavsar / intent-classification
Multiclass Intent Classification using MLP, LSTM, and BERT (subtask: Topic Modelling).
Language:Jupyter Notebook 4vincent10400094 / news-classification
Final project for the course "EE4037 Introduction to Digital Speech Processing" 2020 fall.
Language:Python 4wildlyclassyprince / data-playground
Data analysis projects
Language:Jupyter Notebook 4bacdavid / InfomaxVAE
Obtain the latent variables that contain the maximal mutual information.
Language:Python 3cd-dpk / concept_locator
Concept Locator is to search for the concept in source code. The input is a query representining a concept and output is the ranked list of code locations based on similarity of the concept and the code portion. The implementation is based on the works of Marcus et. al titled "An information retrieval approach to concept location in source code" on 2004 and Gregory et. al. titled "On the use of relevance feedback in IR-based concept location" on 2009.
Language:Java 3- Language:Python 3
jeyadosstimothy / ML-on-CrisisLex
Application of Machine Learning Techniques for Text Classification and Topic Modelling on CrisisLexT26 dataset.
Language:Python 3lrbrwnn1 / HIVE
Django-based web app developed for the UofM Bioinformatics Dept, now in development at Beaumont School of Medicine. Uses latent semantic analysis, text mining and web-scraping to find conceptual similarities ratings between researchers, grants and clinical trials.
Language:JavaScript 3Tritium-Glass / Twitter-Trend-Summarization-Using-Improved-Word-Frequency
Twitter bot that uses an improved word frequency algorithm based on gradient heuristics for extractive summarization
Language:Python 3vahadruya / Capstone-Project-Unsupervised-ML-Topic-Modelling
The project explores a dataset of 2225 BBC News Articles and identifies the major themes and topics present in them. Topic Modeling algorithms such as Latent DIrichlet Allocation and Latent Semantic Analysis have been implemented. Effetiveness of the method of vectorization has also been explored
Language:Jupyter Notebook 3
