We have used the Countvectorizer to convert text into a vector, Cosine Similarity for the recommendation and for review sentiment analysis we have used the Logistic Regression algorithm.

Built a Movie Recommendation System using cosine similarity.

Implement Information Retrieval Models in JAVA

A program that get recommendations according to the target user and movies. -made in 2023

FLIX-HUB is a movie recommendation system utilizing the Netflix dataset. It features comprehensive data preprocessing and analysis, generating personalized movie and TV show suggestions based on TF-IDF vectorization and cosine similarity. The project includes interactive visualizations for insights into content trends and distributions.

Simple statistical functions that are useful for exploratory spatial data analysis (ESDA) on-the-fly in JavaScript

Word Grouping by List Category

DataScience-Statistics,Machine Learning,AppliedAI

Movie Recommendation System using Cosine Similarity

Question Answering Chatbot with DistilRoBERTa Sentence Embeddings, Dialogflow and Ngrok

A utility library for comparing strings via Cosine Similarity

Posts/Feeds recommendation engine based on content based and collaborative filtering methods

Measure performance in calculating cosine similarity: C, C++, Go, Python, Perl and Oberon2.

Implementation of TextRank with the option of using pre-trained Word2Vec embeddings as the similarity metric

对四种句子/文本相似度计算方法进行实验与比较