Gap filled question generator
-
Updated
May 1, 2023 - Python
Gap filled question generator
PDF Notes + Deep Learning -> AI-Generated Slides
Source-Recommendation-System takes an article from the user as input and outputs any relevant article from a dataset of 8.5 million articles.
In this project, I explore a TripAdvisor hotel review dataset with the LDA algorithm, Rapid Keyword Extraktion (RAKE)
👀 A very simple sentence classifier based on word similarity with NLTK and rake_nltk package
Keyword based searching and matching algorithm using Deep NLP
A miniature Java Search Engine using the Rapid Automatic Keyword Extraction Framework ( RAKE ) and HashMaps
A self-contained Java15 implementation of the Rapid Automatic Keyword Extraction Framework ( RAKE ) for keyword extraction.
Automatic keyword extraction methods from individual documents.
"Advertising platform ,find the relevant keywords on blog and then find ads which are relevant to them automatically"
The project is a Python implementation of a Text Summarizer. It uses various natural language processing (NLP) techniques to generate a summary of a given text.
Keyword/entity/phrases identification & a possible approach to map to categories
PDF keyword extraction using Python 3. Extract text from a PDF document and determine key phrases in a body of text by analyzing the frequency of word appearance and its co-occurance with other words in the text.
A movie recommendation web-based application that recommends movies (using a content-based filtering algorithm) to a user.
This Python project shows how to build a content based recommendation system. Data is related to movies.
Add a description, image, and links to the rake-nltk topic page so that developers can more easily learn about it.
To associate your repository with the rake-nltk topic, visit your repo's landing page and select "manage topics."