Graph-partitioning entity resolution for resolving noisy product names in OCR scans of retail receipts

Jose Ramon Ilagan; Joseph Benjamin Ilagan

doi:10.1016/j.procs.2024.06.180

Graph-partitioning entity resolution for resolving noisy product names in OCR scans of retail receipts

Jose Ramon Ilagan
, Joseph Benjamin Ilagan

Department of Quantitative Methods and Information Technology

Ateneo de Manila University

Research output: Contribution to journal › Conference article › peer-review

Original language	English
Pages (from-to)	338-345
Number of pages	8
Journal	Procedia Computer Science
Volume	239
DOIs	https://doi.org/10.1016/j.procs.2024.06.180
State	Published - 2024
Event	2023 International Conference on ENTERprise Information Systems, CENTERIS 2023 - International Conference on Project MANagement, ProjMAN 2023 - International Conference on Health and Social Care Information Systems and Technologies, HCist 2023 - Porto, Portugal Duration: Nov 8 2023 → Nov 10 2023

ASJC Scopus Subject Areas

General Computer Science

Keywords

Agglomerative Clustering
Business Intelligence
Master Data Management
Retail
Retail Analytics
Shopper Insights
Shopping Analytics

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10.1016/j.procs.2024.06.180

Cite this

@article{70a07767778d44b7aa2e23877299c55f,

title = "Graph-partitioning entity resolution for resolving noisy product names in OCR scans of retail receipts",

keywords = "Agglomerative Clustering, Business Intelligence, Master Data Management, Retail, Retail Analytics, Shopper Insights, Shopping Analytics",

author = "Ilagan, \{Jose Ramon\} and Ilagan, \{Joseph Benjamin\}",

note = "Publisher Copyright: {\textcopyright} 2024 The Author(s).; 2023 International Conference on ENTERprise Information Systems, CENTERIS 2023 - International Conference on Project MANagement, ProjMAN 2023 - International Conference on Health and Social Care Information Systems and Technologies, HCist 2023 ; Conference date: 08-11-2023 Through 10-11-2023",

year = "2024",

doi = "10.1016/j.procs.2024.06.180",

language = "English",

volume = "239",

pages = "338--345",

journal = "Procedia Computer Science",

issn = "1877-0509",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - Graph-partitioning entity resolution for resolving noisy product names in OCR scans of retail receipts

AU - Ilagan, Jose Ramon

AU - Ilagan, Joseph Benjamin

PY - 2024

Y1 - 2024

KW - Agglomerative Clustering

KW - Business Intelligence

KW - Master Data Management

KW - Retail

KW - Retail Analytics

KW - Shopper Insights

KW - Shopping Analytics

UR - https://www.scopus.com/pages/publications/85201292311

UR - https://www.scopus.com/pages/publications/85201292311#tab=citedBy

U2 - 10.1016/j.procs.2024.06.180

DO - 10.1016/j.procs.2024.06.180

M3 - Conference article

AN - SCOPUS:85201292311

SN - 1877-0509

VL - 239

SP - 338

EP - 345

JO - Procedia Computer Science

JF - Procedia Computer Science

T2 - 2023 International Conference on ENTERprise Information Systems, CENTERIS 2023 - International Conference on Project MANagement, ProjMAN 2023 - International Conference on Health and Social Care Information Systems and Technologies, HCist 2023

Y2 - 8 November 2023 through 10 November 2023

ER -

Graph-partitioning entity resolution for resolving noisy product names in OCR scans of retail receipts

ASJC Scopus Subject Areas

Keywords

Access to Document

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