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Understanding Scanned Receipts

2020-05-04 20:20:33
Eric Melz
arXiv_CL
         
Abstract

Tasking machines with understanding receipts can have important applications such as enabling detailed analytics on purchases, enforcing expense policies, and inferring patterns of purchase behavior on large collections of receipts. In this paper, we focus on the task of Named Entity Linking (NEL) of scanned receipt line items; specifically, the task entails associating shorthand text from OCR'd receipts with a knowledge base (KB) of grocery products. For example, the scanned item "STO BABY SPINACH" should be linked to the catalog item labeled "Simple Truth Organic Baby Spinach". Experiments that employ a variety of Information Retrieval techniques in combination with statistical phrase detection shows promise for effective understanding of scanned receipt data.

Abstract (translated)

URL

https://arxiv.org/abs/2005.01828

PDF

https://arxiv.org/pdf/2005.01828.pdf

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