Book Suggestion System based on Amazon Book Review Dataset
Amazon Book Reviews: Exploration and Sentiment Analysis
Interesting Examples from Amazon Book Rating Dataset
Product Recommender using Amazon Review dataset
Statistics of the Amazon reviews dataset including the number of
COMMENTS
Amazon review data
Download 233.1 million reviews, product metadata, and links from Amazon.com in various categories and time periods. See citation, news, and colab notebook for data analysis and cleaning.
Introduction
Download 571.54M user reviews, item metadata, links and splits for RecSys benchmarking. Compare with previous versions and explore by category, timestamp and token count.
McAuley-Lab/Amazon-Reviews-2023 · Datasets at Hugging Face
This is a large-scale Amazon Reviews dataset, collected in 2023 by McAuley Lab, and it includes rich features such as: User Reviews ( ratings, text, helpfulness votes, etc.); Item Metadata ( descriptions, price, raw image, etc.); Links ( user-item / bought together graphs).
Amazon Books Reviews
Goodreads-books reviews and descriptions of each book . Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Learn more. OK, Got it. Something went wrong and this page crashed! If the issue persists, it's likely a problem on our side.
amazon_us_reviews
Description: Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website.
Sentiment Analysis of Amazon Reviews
The Amazon reviews full score dataset is constructed by randomly taking 6,00,000 training samples and 1,30,000 testing samples for each review score from 1 to 5. In total there are 30,00,000 training samples and 6,50,000 testing samples. Kaggle Link to the Dataset. Project Structure.
Amazon Review Dataset
Amazon Review is a dataset to tackle the task of identifying whether the sentiment of a product review is positive or negative. This dataset includes reviews from four different merchandise categories: Books (B) (2834 samples), DVDs (D) (1199 samples), Electronics (E) (1883 samples), and Kitchen and housewares (K) (1755 samples).
Amazon Reviews 2018 (Full Dataset)
A full reviews dataset from Amazon including ratings and review text. A full reviews dataset from Amazon including ratings and review text. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Learn more. OK, Got it. Something went wrong and this page crashed! ...
Amazon Book Reviews: Exploration and Sentiment Analysis
The review/score column contains ratings from 0 to 5 for the book. The review/time column contains the time of the given review. The review/summary column contains the summary of a text review. The review/text column contains the full text of a review. Cleaning Up the Amazon Book Reviews Dataset. Before beginning our analysis, let us do a ...
amazon-review-dataset · GitHub Topics · GitHub
Add this topic to your repo. To associate your repository with the amazon-review-dataset topic, visit your repo's landing page and select "manage topics." GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.
luminati-io/Amazon-popular-books-dataset
A Github dataset of the most reviewed and best-selling books on Amazon. This Amazon dataset contains 2269 best-selling books. Each book title on this Amazon dataset has gained 10,000 reader reviews or more, making them stand out as the most popular books available.
NLP: A Complete Sentiment Classification on Amazon Reviews
Step 1: Fundamental preprocessing tasks. Some fundamental text preprocessing steps include lowercasing, punctuations removal, and removal of stopwords. Stopwords are referred to a set of commonly used words such as 'to', 'from', and 'or'. In the NLP approach, these stopwords are perceived as insignificant information, and further ...
Amazon review data
This dataset contains product reviews and metadata from Amazon, including 142.8 million reviews spanning May 1996 - July 2014. This dataset includes reviews (ratings, text, helpfulness votes), product metadata (descriptions, category information, price, brand, and image features), and links (also viewed/also bought graphs). Files.
SNAP: Web data: Amazon reviews
This dataset consists of reviews from amazon. The data span a period of 18 years, including ~35 million reviews up to March 2013. Reviews include product and user information, ratings, and a plaintext review. Note: this dataset contains potential duplicates, due to products whose reviews Amazon merges.
Amazon-Book Benchmark (Recommendation Systems)
The current state-of-the-art on Amazon-Book is SSCF. See a full comparison of 14 papers with code. The current state-of-the-art on Amazon-Book is SSCF. See a full comparison of 14 papers with code. ... Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets.
Recommender Systems Datasets
This is a large-scale Amazon Reviews dataset collected in 2023. This dataset contains 48.19 million items, and 571.54 million reviews from 54.51 million users. Basic statistics. ... Goodreads Book Reviews. These datasets contain reviews from the Goodreads book review website, and a variety of attributes describing the items. Critically, these ...
Amazon Reviews for Sentiment Analysis
A few million Amazon reviews in fastText format. A few million Amazon reviews in fastText format. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Learn more. OK, Got it. Something went wrong and this page crashed! ...
Amazon Reviews Dataset
If the issue persists, it's likely a problem on our side. Kaggle is the world's largest data science community with powerful tools and resources to help you achieve your data science goals.
Neural Network Collaborative Filtering with Amazon Book Reviews
They struggled when it came to consistently analyzing the sentiment of the reviews in our dataset. Flair is a powerful natural language processing toolkit that uses pre-trained models to predict text sentiment. It worked very well on Amazon review data, so Flair was the clear choice to obtain Sentiment values for all User-Book reviews.
Amazon Review Full Benchmark (Sentiment Analysis)
The current state-of-the-art on Amazon Review Full is BERT large. See a full comparison of 9 papers with code. ... Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. Read previous issues. Subscribe. Join the community
Multilingual Amazon Reviews Corpus
Description 🔗︎. We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an ...
Imminent: Inside the Pentagon's Hunt for UFOs Hardcover
Luis "Lue" Elizondo is the former head of the Advanced Aerospace Threat Identification Program (AATIP), the Pentagon unit that researched UFOs, now known as Unidentified Anomalous Phenomena (UAP). Prior to AATIP, Elizondo oversaw counterespionage and counterterrorism investigations worldwide for the Department of Defense, and also worked for the Office of the National Counterintelligence ...
Playing with Reality: How Games Have Shaped Our World ...
Praise for Playing with Reality: "By turns philosophical and polemical, this is a provocative and fascinating book." — The Economist "Absorbing. . . . A revealing look at the hidden role that games have played in human development for centuries." — Kirkus " Playing With Reality is a foreboding prehistory of AI. Clancy conveys how we became so in thrall to gaming that we forgot ...
Amazon review data
Description. This dataset contains product reviews and metadata from Amazon, including 143.7 million reviews spanning May 1996 - July 2014. This dataset includes reviews (ratings, text, helpfulness votes), product metadata (descriptions, category information, price, brand, and image features), and links (also viewed/also bought graphs).
Data Engineering with Python: Work with massive datasets ...
This book is for data analysts, ETL developers, and anyone looking to get started with or transition to the field of data engineering or refresh their knowledge of data engineering using Python. This book will also be useful for students planning to build a career in data engineering or IT professionals preparing for a transition.
Apple 2024 MacBook Air 13″ Laptop with M3 chip: 34.46 cm ...
Apple 2024 MacBook Air 13″ Laptop with M3 chip: 34.46 cm (13.6″) Liquid Retina Display, 8GB Unified Memory, 256GB SSD Storage, Backlit Keyboard, 1080p FaceTime HD Camera, Touch ID- Space Grey : Amazon.in
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100 Best Books of the 21st Century: As voted on by 503 novelists, nonfiction writers, poets, critics and other book lovers — with a little help from the staff of The New York Times Book Review.
Python for Data Analysis: Data Wrangling with pandas ...
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively.
Amazon reviews
34,686,770 Amazon reviews from 6,643,669 users on 2,441,053 products. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Learn more. OK, Got it. Something went wrong and this page crashed! If the issue persists, it's likely a problem on our side.
IMAGES
COMMENTS
Download 233.1 million reviews, product metadata, and links from Amazon.com in various categories and time periods. See citation, news, and colab notebook for data analysis and cleaning.
Download 571.54M user reviews, item metadata, links and splits for RecSys benchmarking. Compare with previous versions and explore by category, timestamp and token count.
This is a large-scale Amazon Reviews dataset, collected in 2023 by McAuley Lab, and it includes rich features such as: User Reviews ( ratings, text, helpfulness votes, etc.); Item Metadata ( descriptions, price, raw image, etc.); Links ( user-item / bought together graphs).
Goodreads-books reviews and descriptions of each book . Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Learn more. OK, Got it. Something went wrong and this page crashed! If the issue persists, it's likely a problem on our side.
Description: Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website.
The Amazon reviews full score dataset is constructed by randomly taking 6,00,000 training samples and 1,30,000 testing samples for each review score from 1 to 5. In total there are 30,00,000 training samples and 6,50,000 testing samples. Kaggle Link to the Dataset. Project Structure.
Amazon Review is a dataset to tackle the task of identifying whether the sentiment of a product review is positive or negative. This dataset includes reviews from four different merchandise categories: Books (B) (2834 samples), DVDs (D) (1199 samples), Electronics (E) (1883 samples), and Kitchen and housewares (K) (1755 samples).
A full reviews dataset from Amazon including ratings and review text. A full reviews dataset from Amazon including ratings and review text. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Learn more. OK, Got it. Something went wrong and this page crashed! ...
The review/score column contains ratings from 0 to 5 for the book. The review/time column contains the time of the given review. The review/summary column contains the summary of a text review. The review/text column contains the full text of a review. Cleaning Up the Amazon Book Reviews Dataset. Before beginning our analysis, let us do a ...
Add this topic to your repo. To associate your repository with the amazon-review-dataset topic, visit your repo's landing page and select "manage topics." GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.
A Github dataset of the most reviewed and best-selling books on Amazon. This Amazon dataset contains 2269 best-selling books. Each book title on this Amazon dataset has gained 10,000 reader reviews or more, making them stand out as the most popular books available.
Step 1: Fundamental preprocessing tasks. Some fundamental text preprocessing steps include lowercasing, punctuations removal, and removal of stopwords. Stopwords are referred to a set of commonly used words such as 'to', 'from', and 'or'. In the NLP approach, these stopwords are perceived as insignificant information, and further ...
This dataset contains product reviews and metadata from Amazon, including 142.8 million reviews spanning May 1996 - July 2014. This dataset includes reviews (ratings, text, helpfulness votes), product metadata (descriptions, category information, price, brand, and image features), and links (also viewed/also bought graphs). Files.
This dataset consists of reviews from amazon. The data span a period of 18 years, including ~35 million reviews up to March 2013. Reviews include product and user information, ratings, and a plaintext review. Note: this dataset contains potential duplicates, due to products whose reviews Amazon merges.
The current state-of-the-art on Amazon-Book is SSCF. See a full comparison of 14 papers with code. The current state-of-the-art on Amazon-Book is SSCF. See a full comparison of 14 papers with code. ... Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets.
This is a large-scale Amazon Reviews dataset collected in 2023. This dataset contains 48.19 million items, and 571.54 million reviews from 54.51 million users. Basic statistics. ... Goodreads Book Reviews. These datasets contain reviews from the Goodreads book review website, and a variety of attributes describing the items. Critically, these ...
A few million Amazon reviews in fastText format. A few million Amazon reviews in fastText format. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Learn more. OK, Got it. Something went wrong and this page crashed! ...
If the issue persists, it's likely a problem on our side. Kaggle is the world's largest data science community with powerful tools and resources to help you achieve your data science goals.
They struggled when it came to consistently analyzing the sentiment of the reviews in our dataset. Flair is a powerful natural language processing toolkit that uses pre-trained models to predict text sentiment. It worked very well on Amazon review data, so Flair was the clear choice to obtain Sentiment values for all User-Book reviews.
The current state-of-the-art on Amazon Review Full is BERT large. See a full comparison of 9 papers with code. ... Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. Read previous issues. Subscribe. Join the community
Description 🔗︎. We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an ...
Luis "Lue" Elizondo is the former head of the Advanced Aerospace Threat Identification Program (AATIP), the Pentagon unit that researched UFOs, now known as Unidentified Anomalous Phenomena (UAP). Prior to AATIP, Elizondo oversaw counterespionage and counterterrorism investigations worldwide for the Department of Defense, and also worked for the Office of the National Counterintelligence ...
Praise for Playing with Reality: "By turns philosophical and polemical, this is a provocative and fascinating book." — The Economist "Absorbing. . . . A revealing look at the hidden role that games have played in human development for centuries." — Kirkus " Playing With Reality is a foreboding prehistory of AI. Clancy conveys how we became so in thrall to gaming that we forgot ...
Description. This dataset contains product reviews and metadata from Amazon, including 143.7 million reviews spanning May 1996 - July 2014. This dataset includes reviews (ratings, text, helpfulness votes), product metadata (descriptions, category information, price, brand, and image features), and links (also viewed/also bought graphs).
This book is for data analysts, ETL developers, and anyone looking to get started with or transition to the field of data engineering or refresh their knowledge of data engineering using Python. This book will also be useful for students planning to build a career in data engineering or IT professionals preparing for a transition.
Apple 2024 MacBook Air 13″ Laptop with M3 chip: 34.46 cm (13.6″) Liquid Retina Display, 8GB Unified Memory, 256GB SSD Storage, Backlit Keyboard, 1080p FaceTime HD Camera, Touch ID- Space Grey : Amazon.in
100 Best Books of the 21st Century: As voted on by 503 novelists, nonfiction writers, poets, critics and other book lovers — with a little help from the staff of The New York Times Book Review.
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively.
34,686,770 Amazon reviews from 6,643,669 users on 2,441,053 products. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Learn more. OK, Got it. Something went wrong and this page crashed! If the issue persists, it's likely a problem on our side.