Amazon Reviews Full

Amazon Review Full Score Dataset<br>Version 3, Updated 09/09/2015<br>ORIGIN<br>The Amazon reviews 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. For more information, please refer to the following paper: J. McAuley and J. Leskovec. Hidden factors and hidden topics: understanding rating dimensions with review text. RecSys, 2013.<br>The Amazon reviews full score dataset is constructed by Xiang Zhang ([e-mail]) from the above dataset. It is used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015).<br><br>DESCRIPTION<br>The Amazon reviews full score dataset is constructed by randomly taking 600,000 training samples and 130,000 testing samples for each review score from 1 to 5. In total there are 3,000,000 trainig samples and 650,000 testing samples.<br>The files train.csv and test.csv contain all the training samples as comma-sparated values. There are 3 columns in them, corresponding to class index (1 to 5), review title and review text. The review title and text are escaped using double quotes ("), and any internal double quote is escaped by 2 double quotes (""). New lines are escaped by a backslash followed with an "n" character, that is "\n".<br>

亚马逊全评分评论数据集（Amazon Review Full Score Dataset）<br>版本3，更新于2015年9月9日<br>源起<br>亚马逊评论数据集收录了亚马逊平台的用户评论，数据覆盖18年时间跨度，截至2013年3月共包含约3500万条评论。每条评论包含商品与用户信息、评分以及纯文本评论内容。更多细节可参考以下论文：J. McAuley与J. Leskovec所著《隐藏因素与隐藏主题：利用评论文本理解评分维度》，发表于2013年推荐系统大会（RecSys 2013）。<br>该亚马逊全评分评论数据集由张翔（[e-mail]）基于上述原始数据集构建，并被用作以下论文中的文本分类基准数据集：Xiang Zhang、Junbo Zhao、Yann LeCun所著《用于文本分类的字符级卷积网络》，发表于2015年《神经信息处理系统进展》第28卷（NIPS 2015）。<br>数据集说明<br>该数据集针对1至5的每一个评分等级，分别随机抽取60万条训练样本与13万条测试样本，总计包含300万条训练样本与65万条测试样本。<br>训练文件"train.csv"与测试文件"test.csv"以逗号分隔值（Comma-Separated Values，简称CSV）格式存储全部样本，每个文件包含3列数据，分别对应分类索引（1至5）、评论标题与评论正文。评论标题与正文采用双引号进行转义，若文本内部包含双引号，则需使用两个连续双引号（""）进行转义；换行符则通过反斜杠加小写字母n（
）实现转义。