A day to day plan for this challenge. Covers both theoritical and practical aspects

TextRank implementation for C#

A Dataset for Thai Text Summarization with over 310K articles.

A writer that can generate news after a game using live texts.

Using Spacy and NLTK module with Tf-Idf algorithm for text-summarisation. This code will give you the summary of inputted article. You can input text directly or from .txt file, .pdf file or from wikipedia url.

针对LCSTS数据集，目前有两种预处理方式。

various ways to summarise text using the libraries available for Python: pyteaser, sumy, gensim, pytldr, XLNET, BERT, and GPT2.

A Hiphop v. Literature project to demonstrate using NLP that Hip-Hop is a form of literature and rap artists are literary geniuses.

Document based ChatGPT

This notebook leverages Transfer Learning Algorithms and standard NLP procedures to summarize a given paragraph meaningfully.

Text summarization is the problem of creating a short, accurate, and fluent summary of a longer text document

PDF Text Summarization and Q&A Chatbot This project is a Streamlit-based web application that allows users to upload PDF documents, extract and summarize their text content, and interact with a Q&A chatbot to get answers related to the document.

LongT5-based model pre-trained on a large amount of unlabeled Vietnamese news texts and fine-tuned with ViMS and VMDS collections

SumSimple is a FastAPI-based text summarization service using traditional, non-LLM algorithms like SumBasic, Luhn, Edmundson, LexRank, TextRank, and LSA.

Cet article passe en revue l'analyse sémantique latente (LSA), une théorie de la signification ainsi qu'une méthode pour extraire ce sens de passages de texte, basée sur des statistiques calculs sur un ensemble de documents. LSA comme théorie du sens définit un espace sémantique latent où les documents et les mots individuels sont représentés so…

文本摘要 + TextRank4 + docker

A personal project that explores the text mining capabilities of the (tm) package in R

This website utilizes the Hugging Face API to generate image descriptions based on user-provided text input. The application is built with HTML, CSS, and JavaScript, and it leverages the facebook/bart-large-cnn model for generating textual summaries.

Implementation of Large Language Model in NER, text summarization, sentimen analysis in Python