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arxiv 2208.07130 v1 pith:7PTXE4HD submitted 2022-08-15 cs.CL cs.IR

Exploring Generative Models for Joint Attribute Value Extraction from Product Titles

classification cs.CL cs.IR
keywords generativeattributeextractionproductsequence-basedtaskvaluevalues
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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