Unsupervised Anomaly Detection in Receipt Data
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Student thesisAlternative title
Oövervakad anomalidetektion i kvittodata (Swedish)
Abstract [en]
With the progress of data handling methods and computing power comes the possibility of automating tasks that are not necessarily handled by humans. This study was done in cooperation with a company that digitalizes receipts for companies. We investigate the possibility of automating the task of finding anomalous receipt data, which could automate the work of receipt auditors. We study both anomalous user behaviour and individual receipts. The results indicate that automation is possible, which may reduce the necessity of human inspection of receipts.
Abstract [sv]
Med de framsteg inom datahantering och datorkraft som gjorts så kommer också möjligheten att automatisera uppgifter som ej nödvändigtvis utförs av människor. Denna studie gjordes i samarbete med ett företag som digitaliserar företags kvitton. Vi undersöker möjligheten att automatisera sökandet av avvikande kvittodata, vilket kan avlasta revisorer. Vti studerar både avvikande användarbeteenden och individuella kvitton. Resultaten indikerar att automatisering är möjligt, vilket kan reducera behovet av mänsklig inspektion av kvitton
Place, publisher, year, edition, pages
2017. , p. 52
Keywords [en]
Anomaly detection, receipt, unsupervised
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-215161OAI: oai:DiVA.org:kth-215161DiVA, id: diva2:1146710
External cooperation
Skovik
Subject / course
Computer Science
Educational program
Master of Science in Engineering -Engineering Physics
Supervisors
Examiners
2017-10-192017-10-032022-06-27Bibliographically approved