tianchi_mobile_recommend

In real business scenarios, we often need to build personalized recommendation models for a subset of all products. In the process of completing this task, we not only need to utilize user behavior data on this subset of products, but also often need to utilize richer user behavior data. Define the following symbols: U - User Collection I - Complete Collection of Products P - Product subset, P ⊆ I D - User behavior data set for the complete set of products So our goal is to use D to construct a recommendation model for U users to P products.

搜集汇总

背景与挑战

背景概述

该数据集是一个用于构建个性化推荐模型的数据集，重点关注用户行为数据和产品子集。它包含8.90 MB的数据，适用于计算机科学和信息技术等领域的研究和应用。