Using Classification Algorithms for Smart Suggestions in Accounting Systems

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dc.contributor.authorBengtsson, Hampus
dc.contributor.authorJansson, Johannes
dc.contributor.departmentChalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)sv
dc.contributor.departmentChalmers University of Technology / Department of Computer Science and Engineering (Chalmers)en
dc.date.accessioned2019-07-03T13:42:46Z
dc.date.available2019-07-03T13:42:46Z
dc.date.issued2015
dc.description.abstractAccounting is a repetitive task and is mainly done manually. The repetitiveness makes it a suitable target for automation, however not much research has been done in the area yet. This thesis investigates how two di erent classification algorithms, Support Vector Machine with Stochastic Gradient Descent training and a Feed-Forward Neural Network, perform at classifying nancial transactions based on historical data in an accounting context. The classification algorithms show promising results but still does not outperform the existing implementation which is simple and deterministic. However, classi cation itself very much relies on the labels, i.e. how different users have accounted the transactions. As a response to this, we finally give a suggestion on how clustering might be used for the automation of accounting instead.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/219162
dc.language.isoeng
dc.setspec.uppsokTechnology
dc.subjectData- och informationsvetenskap
dc.subjectInformations- och kommunikationsteknik
dc.subjectComputer and Information Science
dc.subjectInformation & Communication Technology
dc.titleUsing Classification Algorithms for Smart Suggestions in Accounting Systems
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
dc.type.uppsokH
local.programmeComputer science – algorithms, languages and logic (MPALG), MSc
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