Content-based-Recommender-System
It is a content based recommender system that uses tf-idf and cosine similarity for N Most SImilar Items from a dataset
nikitaa30 / Content-based-Recommender-System
Licence: other
It is a content based recommender system that uses tf-idf and cosine similarity for N Most SImilar Items from a dataset
Stars: ✭ 64
Programming Languages
python
139335 projects - #7 most used programming language
Projects that are alternatives of or similar to Content-based-Recommender-System
bns-short-text-similarity
📖 Use Bi-normal Separation to find document vectors which is used to compute similarity for shorter sentences.
Stars: ✭ 24 (-62.5%)
Mutual labels: tf-idf, cosine-similarity
koolsla
Food recommendation tool with Machine learning.
Stars: ✭ 21 (-67.19%)
Mutual labels: tf-idf, cosine-similarity
Recommender-Systems
Implementing Content based and Collaborative filtering(with KNN, Matrix Factorization and Neural Networks) in Python
Stars: ✭ 46 (-28.12%)
Mutual labels: tf-idf, recommender-system
Textvec
Text vectorization tool to outperform TFIDF for classification tasks
Stars: ✭ 167 (+160.94%)
Mutual labels: tf-idf
Cadmium
Natural Language Processing (NLP) library for Crystal
Stars: ✭ 172 (+168.75%)
Mutual labels: tf-idf
ResumeRise
An NLP tool which classifies and summarizes resumes
Stars: ✭ 29 (-54.69%)
Mutual labels: tf-idf
Recommendation-based-on-sequence-
Recommendation based on sequence
Stars: ✭ 23 (-64.06%)
Mutual labels: recommender-system
Document-Classification-using-LSA
Document classification using Latent semantic analysis in python
Stars: ✭ 16 (-75%)
Mutual labels: tf-idf
slopeone
PHP implementation of the Weighted Slope One rating-based collaborative filtering scheme.
Stars: ✭ 85 (+32.81%)
Mutual labels: recommender-system
Textclassification
several methods for text classification
Stars: ✭ 180 (+181.25%)
Mutual labels: tf-idf
RecommenderSystemsNotebooks
Set of notebooks analysing and discussing the ideas presented at Coursera's Recommender Systems course
Stars: ✭ 28 (-56.25%)
Mutual labels: recommender-system
KeywordExtraction
Implementation of algorithm in keyword extraction,including TextRank,TF-IDF and the combination of both
Stars: ✭ 95 (+48.44%)
Mutual labels: tf-idf
SSE-PT
Codes and Datasets for paper RecSys'20 "SSE-PT: Sequential Recommendation Via Personalized Transformer" and NurIPS'19 "Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers"
Stars: ✭ 103 (+60.94%)
Mutual labels: recommender-system
Snowball
Implementation with some extensions of the paper "Snowball: Extracting Relations from Large Plain-Text Collections" (Agichtein and Gravano, 2000)
Stars: ✭ 131 (+104.69%)
Mutual labels: tf-idf
disentangled graph collaborative filtering
Disentagnled Graph Collaborative Filtering, SIGIR2020
Stars: ✭ 118 (+84.38%)
Mutual labels: recommender-system
GNN-Recommendation
毕业设计：基于图神经网络的异构图表示学习和推荐算法研究
Stars: ✭ 52 (-18.75%)
Mutual labels: recommender-system
NGCF-PyTorch
PyTorch Implementation for Neural Graph Collaborative Filtering
Stars: ✭ 200 (+212.5%)
Mutual labels: recommender-system
pygrams
Extracts key terminology (n-grams) from any large collection of documents (>1000) and forecasts emergence
Stars: ✭ 52 (-18.75%)
Mutual labels: tf-idf
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].