Graph-Partitioning Entity Resolution for Resolving Noisy Product Names in OCR Scans of Retail Receipts

Graph-Partitioning Entity Resolution for Resolving Noisy Product Names in OCR Scans of Retail Receipts

In business intelligence for retail, it is critical to ensure consistent and unambiguous product dimension information. This is challenging, especially if an organization does not have full control over the source of either transaction or master data. Such lack of control is the case when brands rel...

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Bibliographic Details
Main Authors: Ilagan, Jose Ramon, Ilagan, Joseph Benjamin R
Format: text
Published: Archīum Ateneo 2024
Subjects:
Agglomerative Clustering
Business Intelligence
Master Data Management
Retail
Retail Analytics
Shopper Insights
Shopping Analytics
Business
Computer Sciences
Physical Sciences and Mathematics
Online Access:https://archium.ateneo.edu/qmit-faculty-pubs/26
https://archium.ateneo.edu/context/qmit-faculty-pubs/article/1025/viewcontent/1_s2.0_S1877050924014236_main.pdf
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Institution: Ateneo De Manila University

Internet

https://archium.ateneo.edu/qmit-faculty-pubs/26
https://archium.ateneo.edu/context/qmit-faculty-pubs/article/1025/viewcontent/1_s2.0_S1877050924014236_main.pdf

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