Topic: product-reviews Goto Github
Some thing interesting about product-reviews
Some thing interesting about product-reviews
product-reviews,Implementation of machine Learning algorithms to perform analysis like- Predictive and Sentiment analysis.
User: ach30
product-reviews,Sentiment analysis with ML to classify customers purchase reviews
User: ahjimomo
product-reviews,Sentiment analysis model for ranking product reviews, highlighting the most relevant ones while pushing down less relevant or irrelevant reviews using pairwise ranking.
User: ajnavneet
product-reviews,Sentiment analysis of Flipkart reviews. Predict ratings. Dublin Business School research.
User: ajuremesh
product-reviews,sentiment and part of speech analysis on product reviews
User: akokotis
product-reviews,Using a product review dataset to 1. create a chatbot that conducts analysis on command, 2. create predictive models to construct a consumer chatbot to enhance the review giving process and 3. Use feature engineering to extract aspects or unique and most relevant feedback from positive and negative reviews
User: ambikaa-jaggi
product-reviews,Sentiment analysis on product reviews with identification of most reviewed products from Amazon product reviews dataset consists of 35000 reviews.
User: arjun-mota
product-reviews,Review Scraper Project implemented using Python.
User: chandrakant817
product-reviews,Reference implementation of product reviews using Episerver Social
Organization: episerver
Home Page: http://world.episerver.com/documentation/developer-guides/social/
product-reviews,Fera.ai Magento 2 Extension
Organization: feracommerce
product-reviews,Fully connected neural network analyzing sentiments in reviews for Amazon's Alexa.
User: guilhermedom
product-reviews,I built Sentiment Analysis models leveraging a deep learning approach utilizing the customer reviews of Amazon products. Since Long Short Term Memory Network (LSTM) is very effective in dealing with long sequence data and learning long-term dependencies, I used it for automatic sentiment classification of future product reviews.
User: hardikasnani
product-reviews,This is a full stack eCommerce website built using the PERN stack (PostgreSQL, Express, React, Node.js). It features a modern and responsive design, secure payment gateways, dynamic product display algorithms, and comprehensive user functionalities such as wishlist, reviews, order tracking, and more.
User: harmanpreet-singh-xyt
Home Page: https://harman-ecommerce.vercel.app
product-reviews,A Full Stack E-Commerce Application developed using MERN Stack deployed on Heroku. Backend is functional with Admin & Protect Middleware for access Protected Routes. Frontend Centralized with Redux Store.
User: hemantsaini-7
product-reviews,AI product reviewer - Mini Project sem IV CE
User: hitstar53
Home Page: https://ai-product-reviewer-production.up.railway.app/
product-reviews,source code for signed bipartite graph neural networks(CIKM 2021)
User: huangjunjie-cs
Home Page: https://arxiv.org/abs/2108.09638
product-reviews,This repository includes a web application that is connected to a product recommendation system developed with the comprehensive Amazon Review Data (2018) dataset, consisting of nearly 233.1 million records and occupying approximately 128 gigabytes (GB) of data storage, using MongoDB, PySpark, and Apache Kafka.
User: huzaifakhan04
product-reviews,This repository showcases the outcomes of an Exploratory Data Analysis (EDA), including visualisation, conducted on the comprehensive Amazon Review Data (2018) dataset, consisting of nearly 233.1 million records and occupying approximately 128 gigabytes (GB) of data storage, using MongoDB and PySpark.
User: huzaifakhan04
product-reviews,Using Machine Learning to Analyze & Visualize Consumer Behavior
User: jbenasuli
Home Page: https://jbenasuli.github.io/consumer_behavior/
product-reviews,Opinion Extraction based on Amazon Reviews
User: jinwangjoshua
Home Page: https://www.amazon.com/
product-reviews,Model performing sentiment analysis and exploring text pre-processing techniques on product reviews (based on SpyCy)
User: jsymonowicz
product-reviews,System for irony detection in product reviews
User: kbuschme
product-reviews,this is my repository for Amazon review helpfulness prediction model
User: keisukeirie
product-reviews,Creating customers an excellent product experience will lead to compliments, where powerful mouth-of-word was born to improve your sales performance. Reviews are also the type of “mouth-of-word” in the Net in order to test product’s quality.
User: landofcoder
Home Page: https://landofcoder.com/advanced-magento-2-product-reviews.html/
product-reviews,Like reviews, only way better.
Organization: liquidweb
product-reviews,Magento 2 Better Product Reviews GraphQL is now a part of the Mageplaza Better Product Reviews extension that adds GraphQL features. This is helpful for PWA compatibility. The module provides type and resolver information for the GraphQl module to generate catalog review information endpoints.
Organization: mageplaza
Home Page: https://www.mageplaza.com/magento-2-better-product-reviews/
product-reviews,Magento 2 Extension to restrict addition of product review to those customers who purchased the product | Manish Joy
User: manishjoy
Home Page: https://manishjoy.github.io/
product-reviews,Lightweight website to review a product.
User: marvelmiles
Home Page: https://marvelmiles.github.io/advent
product-reviews,A web application to share reviews on services and products by consumers. Here consumers could post, search and read reviews in an organized and optimized way. It was helpful to get an insight over a service or product before availing it. It was a part of a citizen involvement experiment. We tested the application at the campus of LUT, FInland.
User: mdtawseef
product-reviews,Web scraping product reviews data from AliExpress.
User: mohammedderouiche
product-reviews,This repository is all about creating the framework for the digital banking
Organization: onlinepractice
product-reviews,This dataset of online customer reviews in Turkish has been prepared for academic use.
User: ozgekervan
product-reviews,A customer feedback demo application for collecting reviews for a product after a successful purchase.
User: pecrio
Home Page: product-review-and-management-demo-app.vercel.app
product-reviews,Sentiment Analysis of product based reviews using Machine Learning Approaches. This is my Final Year B.Tech Project, 2018.
User: pranitbose
product-reviews,Understanding the sentiment of customers from product reviews using IndicBERT
User: praths71018
product-reviews,Emotionally Aware Chatbot (EAC) for Responding to Indonesian Product Reviews
User: rhiosutoyo
product-reviews,Back-end: https://github.com/ricardohuaripata/ASHON-Ecommerce-API
User: ricardohuaripata
Home Page: https://ricardohuaripata.com/projects/ashon-ecommerce
product-reviews,We employ a text content analysis framework that has been successful in other studies to identify important features of automobile service parts
User: rudrakshsyal
Home Page: https://rsyal.shinyapps.io/RShinyApplication/
product-reviews,This is a multi - vendor e - commerce website. Built with all cool features, wide range of products, invoice generations, vendor and admin portals, online payments and much more!
User: rushabhkela
Home Page: https://ezshopping-rushabh.herokuapp.com
product-reviews,Data Science - Text Mining Work
User: saikrishnabudi
product-reviews,Perform sentimental analysis on the Elon-musk tweets and Extract reviews of any product from ecommerce website like amazon, Perform emotion mining.
User: shanuhalli
product-reviews,The system deletes fake reviews on products and rates a product automatically based on customer reviews
User: shivananda199
product-reviews,An automatically annotated sentiment analysis dataset of product reviews in Russian.
User: sismetanin
product-reviews,👩💻“Don’t do it for the money, do it because you love it!”Sound familiar?⏳ Sounds great, right?📡
User: storieswithsiva
Home Page: https://www.linkedin.com/in/iamsivab
product-reviews,Get Aliexpress product details as a json response including feedbacks, variants, shipping info, description, images, etc.,
User: sudheer-ranga
product-reviews,Fall 2020 DS4A Project: AWS
User: tashakim
product-reviews,The objective of the project is to detect the underlying sentiments of the product reviews. Classifying the reviews as positive, negative and neutral helps to determine the overall emotion behind the product and assist business strategies.
User: ugr-gowthamraj
product-reviews,Text-Mining-Amazon-Reviews-using-Scrapy. Ever wondered? Life would be easier if there could be ways to know how well your product performs and what do people feel about your product? The Solution -Text Mining Techniques. https://medium.com/@vaitybharati/text-mining-how-to-extract-amazon-reviews-using-scrapy-5bd709cb826c
User: vaitybharati
product-reviews,Sentiment Analysis using LSTM cells on Recurrent Networks. GloVe word embeddings were used for vector representation of words. Amazon Product Reviews were used as Dataset.
User: vishwassathish
product-reviews,helpfulness prediction online product review
User: yinfeiy
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