MMRec：简化多模态推荐
MMRec: Simplifying Multimodal Recommendation
AI总结：
MMRec是一个开源工具箱，旨在简化多模态推荐模型的实现与比较，提供统一可配置平台，支持从矩阵分解到图算法的多模态融合，并公开源代码。
摘要：
本文介绍了一个开源工具箱MMRec，用于多模态推荐。MMRec简化并规范了实现和比较多模态推荐模型的过程。MMRec的目标是提供一个统一且可配置的平台，以最小化实现和测试多模态推荐模型的工作量。它支持从传统矩阵分解到现代基于图的算法等多模态模型，能够同时融合来自多个模态的信息。我们的文档、示例和源代码可在https://github.com/enoche/MMRec获取。
英文摘要：
This paper presents an open-source toolbox, MMRec for multimodal recommendation. MMRec simplifies and canonicalizes the process of implementing and comparing multimodal recommendation models. The objective of MMRec is to provide a unified and configurable arena that can minimize the effort in implementing and testing multimodal recommendation models. It enables multimodal models, ranging from traditional matrix factorization to modern graph-based algorithms, capable of fusing information from multiple modalities simultaneously. Our documentation, examples, and source code are available at \url{https://github.com/enoche/MMRec}.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
