TMVishnu/watch-market-gnn

该数据集将传统的手表市场数据转换为图神经网络（GNN）结构，旨在捕捉二手奢侈品手表市场的复杂动态。数据集包含三个关键市场特征：基于条件的价值动态、时间价格行为和模型间关系。数据集的结构包括节点特征张量、边索引矩阵和边属性。数据集的主要用途包括高级手表推荐系统、市场定位分析、价值关系建模和时间趋势分析。

This dataset transforms traditional watch market data into a Graph Neural Network (GNN) structure, specifically designed to capture the complex dynamics of the pre-owned luxury watch market. It addresses three key market characteristics: condition-based value dynamics, temporal price behaviors, and inter-model relationships. The dataset is structured with node features tensor, edge index matrix, and edge attributes. Primary use cases include advanced watch recommendation systems, market positioning analysis, value relationship modeling, and temporal trend analysis.