Understanding Scanned Receipts
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.
Code (0)
등록된 구현이 없습니다.
Tasks
Entity LinkingInformation RetrievalRetrievalSimilar Papers 제목 키워드 기반
ICDAR2019 Competition on Scanned Receipt OCR and Information Extraction
Scanned receipts OCR and key information extraction (SROIE) represent the processeses of recognizing text from scanned receipts and extracting key texts from them and save the extracted tests to structured documents. SRO…
Key Information ExtractionOptical Character Recognition (OCR)Task 2Deep Learning Approach for Receipt Recognition
Inspired by the recent successes of deep learning on Computer Vision and Natural Language Processing, we present a deep learning approach for recognizing scanned receipts. The recognition system has two main modules: tex…
DecoderDeep LearningOptical Character Recognition (OCR)Text DetectionAbstractive Information Extraction from Scanned Invoices (AIESI) using End-to-end Sequential Approach
Recent proliferation in the field of Machine Learning and Deep Learning allows us to generate OCR models with higher accuracy. Optical Character Recognition(OCR) is the process of extracting text from documents and scann…
Optical Character RecognitionOptical Character Recognition (OCR)AMuRD: Annotated Arabic-English Receipt Dataset for Key Information Extraction and Classification
The extraction of key information from receipts is a complex task that involves the recognition and extraction of text from scanned receipts. This process is crucial as it enables the retrieval of essential content and o…
ClassificationKey Information ExtractionLanguage ModellingRetrievalDetecting multi-timescale consumption patterns from receipt data: A non-negative tensor factorization approach
Understanding consumer behavior is an important task, not only for developing marketing strategies but also for the management of economic policies. Detecting consumption patterns, however, is a high-dimensional problem …
ManagementMarketingRhythm