OpenTable data with multi-criteria ratings

With the development of recommender systems (RSs), several promising systems have emerged, such as context-aware RS, multi-criteria RS, and group RS. Multi-criteria recommender systems (MCRSs) are designed to provide personalized recommendations by considering user preferences in multiple attributes or criteria simultaneously. Unlike traditional RSs that typically focus on a single rating, these systems help users make more informed decisions by considering their diverse preferences and needs across various dimensions. In this article, we release the OpenTable data set which was crawled from OpenTable.com. The data set can be considered as a benchmark data set for multi-criteria recommendations.

搜集汇总

背景与挑战

背景概述

该数据集是从OpenTable.com爬取的多标准餐厅评分数据，包含总体评分和食物质量、服务满意度、氛围、整体价值四个维度的评分，共19,536条评分、1,309个用户和91家餐厅，可作为多标准推荐系统的基准数据集。