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电子商务中ID表示的学习和传递

Learning and Transferring IDs Representation in E‑commerce
课程网址: http://videolectures.net/kdd2018_zhao_representation_e-commerce/  
主讲教师: Kui Zhao
开课单位: 阿里巴巴集团
开课时间: 2018-11-23
课程语种: 英语
中文简介:
电子商务中开发了许多机器智能技术,其中最重要的组件之一是ID的表示,包括用户ID、商品ID、产品ID、商店ID、品牌ID、类别ID等,并且它不能反映ID之间的关系,无论是同质的还是异质的。在本文中,我们提出了一种基于嵌入的框架来学习和传递ID的表示。作为用户的隐性反馈,可以很容易地从交互会话中收集到大量的项目ID序列。通过联合使用这些信息序列和ID之间的结构连接,所有类型的ID都可以嵌入到一个低维语义空间中。随后,在四个场景中使用和转移所学习的表示:(i)测量项目之间的相似性,(ii)从可见项目转移到不可见项目,(iii)跨不同域转移,(iv)跨不同任务转移。我们在盒马App中部署并评估了所提出的方法,结果验证了其有效性。
课程简介: Many machine intelligence techniques are developed in E-commerce and one of the most essential components is the representation of IDs, including user ID, item ID, product ID, store ID, brand ID, category ID etc. The classical encoding based methods (like onehot encoding) are inefficient in that it suffers sparsity problems due to its high dimension, and it cannot reflect the relationships among IDs, either homogeneous or heterogeneous ones. In this paper, we propose an embedding based framework to learn and transfer the representation of IDs. As the implicit feedbacks of users, a tremendous amount of item ID sequences can be easily collected from the interactive sessions. By jointly using these informative sequences and the structural connections among IDs, all types of IDs can be embedded into one low-dimensional semantic space. Subsequently, the learned representations are utilized and transferred in four scenarios: (i) measuring the similarity between items, (ii) transferring from seen items to unseen items, (iii) transferring across different domains, (iv) transferring across different tasks. We deploy and evaluate the proposed approach in Hema App and the results validate its effectiveness.
关 键 词: onehot编码; 盒马App; 低维语义空间; 电子商务; ID表示的学习和传递
课程来源: 视频讲座网
数据采集: 2023-03-09:cyh
最后编审: 2023-05-15:cyh
阅读次数: 24