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.",

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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 - http://www.scopus.com/inward/record.url?scp=85201292311&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85201292311&partnerID=8YFLogxK

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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