OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

Wolfram Language (aka Mathematica) paclet with a software monad for Latent Semantic Analysis.

Repository for the project of Information Retrieval

Implementation of various Extractive Text Summarization algorithms.

GANalyzer: Analysis and Manipulation of GANs Latent Space for Controllable Face Synthesis

Extreme Extractive Text Summarization and Topic Modeling (using LSA and LDA techniques) over Reddit Posts from TLDRHQ dataset.

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.

Supplementary Material B: "Mapping the main streams and foci of competence-based education research: A review with direct citation network analysis and topic modelling with latent semantic analysis"

Retrieval of Semantically Relevant Documents using Latent Semantic Analysis

This project showcases an end-to-end workflow for topic modeling and text analysis using a variety of machine learning and natural language processing techniques. The goal of this project is to extract meaningful topics from a collection of text documents, enabling insights, categorization, and understanding of the underlying themes in the data.

Hard-Forked from JuliaText/TextAnalysis.jl

Simple chatbot prototype with Latent Semantic Analysis

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

ICCV23 "Householder Projector for Unsupervised Latent Semantics Discovery"

A Project on Topic Modeling using alogoriths like LSA/LSI, LDA, NMF on RACE dataset

Comparative analysis of emotion detection using BERT and LSA on a shared dataset.

Coding challenge for a BMW job interview involving: 1) an ensemble of supervised binary classifiers; 2) unsupervised outlier detection of text data, dimensionality reduction, and nearest neighbor search

Multiclass Intent Classification using MLP, LSTM, and BERT (subtask: Topic Modelling).

Applying different models for query searching (information retrieving)

In this project, task involves analyzing the content of the articles to extract key concepts and themes that are discussed across the articles to identify major themes/topics across a collection of BBC news articles.