论文标题
探索从产品标题中提取的联合属性值提取的生成模型
Exploring Generative Models for Joint Attribute Value Extraction from Product Titles
论文作者
论文摘要
产品的属性值是任何电子商务平台中必不可少的组成部分。属性值提取（AVE）涉及从其标题或描述中提取产品的属性及其值。在本文中，我们建议使用生成框架来解决AVE任务。我们通过将AVE任务作为生成问题提出，即基于单词序列的生成范式，即基于单词序列和位置序列。我们在两个数据集上进行实验，在该数据集中，生成方法实现了新的最新结果。这表明我们可以将建议的框架用于AVE任务，而无需其他标记或特定于任务的模型设计。
Attribute values of the products are an essential component in any e-commerce platform. Attribute Value Extraction (AVE) deals with extracting the attributes of a product and their values from its title or description. In this paper, we propose to tackle the AVE task using generative frameworks. We present two types of generative paradigms, namely, word sequence-based and positional sequence-based, by formulating the AVE task as a generation problem. We conduct experiments on two datasets where the generative approaches achieve the new state-of-the-art results. This shows that we can use the proposed framework for AVE tasks without additional tagging or task-specific model design.
