KoBERTopic은 BERTopic을 한국어 데이터에 적용할 수 있도록 토크나이저와 BERT를 수정한 코드입니다.

We created a topic modeling pipeline to evaluate different topic modeling algorithms, including their performance on short and long text, preprocessed and not preprocessed datasets, and with different embedding models. Finally, we summarized the results and suggested how to choose algorithms based on the task.

BERTopic 中文使用範例

Slides, Notebook and Data for Presentation: DataHour: Harnessing ML and NLP for Elevated Customer Experiences

This project involved analysing the collected dataset about people experiencing insomnia. This repository contains the code to construct a dataset using the Twitter API, then some data should be annotated with sentiments which is used for training transformer models. The data can be clustered into topics for further analysis with BERTopic.

HDBSCAN Tuning for BERTopic Models

Natural Language Processing with Twitter data

Build interactive topic modeling pipelines.

Scrape website content and extract topics

A Project on Temporal Topic Modeling

A data visualization dashboard powered by Dash framework & Python for Higher Education Institution (HEI) Online Reputation System (Final Year Project)

Aspect Based Sentiment Analysis (ABSA) of Customer Reviews

This projects contains a nlp pipeline for topic labelling with BERTopic

Data Science and Machine Learning projects

Adapted BERTopic pipeline for Topic Modeling the arXiv dataset

This is my final year project "customer reviews classification and analysis system using data mining and nlp". It analyzes and then classifies the customer reviews on the basis of their fakeness, sentiments, contexts and topics discussed. The reviews are taken from various e-commerce platforms like daraz and amazon.

Submission for CL4HEALTH @ LREC-COLING 2024

Code relating to work carried out during an internship at Sinch, consisting of an analysis of current topic modeling models.

Topic modeling for NYT articles.

Use Siebert and BERTopic Model on Persian Dataset