Matches in SemOpenAlex for { <https://semopenalex.org/work/W1514675060> ?p ?o ?g. }
Showing items 1 to 69 of
69
with 100 items per page.
- W1514675060 abstract "This paper describes our efforts to apply various advanced supervised machine learning and natural language processing techniques, including Binomial Logistic Regression, Support Vector Machines, Neural Networks, Ensemble Techniques, and Latent Dirichlet Allocation (LDA), to the problem of detecting fraud in financial reporting documents available from the United States’ Security and Exchange Commission EDGAR database. Specifically, we apply LDA to a collection of type 10-K financial reports and to generate document-topic frequency matrix, and then submit these data to a series of advanced classification algorithms. We then apply evaluation metrics, such as Precision, Receiver Operating Characteristic Curve, and Area Under the Curve to evaluate the performance of each algorithm. We conclude that these methods show promise and suggest applying the approach to a larger set of input documents." @default.
- W1514675060 created "2016-06-24" @default.
- W1514675060 creator A5047212939 @default.
- W1514675060 creator A5050046506 @default.
- W1514675060 creator A5051041400 @default.
- W1514675060 date "2015-04-24" @default.
- W1514675060 modified "2023-09-27" @default.
- W1514675060 title "Detection of fraudulent financial reports with machine learning techniques" @default.
- W1514675060 cites W2158339117 @default.
- W1514675060 doi "https://doi.org/10.1109/sieds.2015.7117005" @default.
- W1514675060 hasPublicationYear "2015" @default.
- W1514675060 type Work @default.
- W1514675060 sameAs 1514675060 @default.
- W1514675060 citedByCount "4" @default.
- W1514675060 countsByYear W15146750602016 @default.
- W1514675060 countsByYear W15146750602020 @default.
- W1514675060 countsByYear W15146750602021 @default.
- W1514675060 countsByYear W15146750602022 @default.
- W1514675060 crossrefType "proceedings-article" @default.
- W1514675060 hasAuthorship W1514675060A5047212939 @default.
- W1514675060 hasAuthorship W1514675060A5050046506 @default.
- W1514675060 hasAuthorship W1514675060A5051041400 @default.
- W1514675060 hasConcept C119857082 @default.
- W1514675060 hasConcept C12267149 @default.
- W1514675060 hasConcept C124101348 @default.
- W1514675060 hasConcept C154945302 @default.
- W1514675060 hasConcept C171686336 @default.
- W1514675060 hasConcept C177264268 @default.
- W1514675060 hasConcept C199360897 @default.
- W1514675060 hasConcept C41008148 @default.
- W1514675060 hasConcept C500882744 @default.
- W1514675060 hasConcept C50644808 @default.
- W1514675060 hasConceptScore W1514675060C119857082 @default.
- W1514675060 hasConceptScore W1514675060C12267149 @default.
- W1514675060 hasConceptScore W1514675060C124101348 @default.
- W1514675060 hasConceptScore W1514675060C154945302 @default.
- W1514675060 hasConceptScore W1514675060C171686336 @default.
- W1514675060 hasConceptScore W1514675060C177264268 @default.
- W1514675060 hasConceptScore W1514675060C199360897 @default.
- W1514675060 hasConceptScore W1514675060C41008148 @default.
- W1514675060 hasConceptScore W1514675060C500882744 @default.
- W1514675060 hasConceptScore W1514675060C50644808 @default.
- W1514675060 hasLocation W15146750601 @default.
- W1514675060 hasOpenAccess W1514675060 @default.
- W1514675060 hasPrimaryLocation W15146750601 @default.
- W1514675060 hasRelatedWork W1554459282 @default.
- W1514675060 hasRelatedWork W1558339584 @default.
- W1514675060 hasRelatedWork W2031275055 @default.
- W1514675060 hasRelatedWork W2098573517 @default.
- W1514675060 hasRelatedWork W2105987408 @default.
- W1514675060 hasRelatedWork W2122730341 @default.
- W1514675060 hasRelatedWork W2123546507 @default.
- W1514675060 hasRelatedWork W2153214340 @default.
- W1514675060 hasRelatedWork W2373555655 @default.
- W1514675060 hasRelatedWork W2395938203 @default.
- W1514675060 hasRelatedWork W2407862841 @default.
- W1514675060 hasRelatedWork W2523487706 @default.
- W1514675060 hasRelatedWork W2590489721 @default.
- W1514675060 hasRelatedWork W2794075952 @default.
- W1514675060 hasRelatedWork W2908297977 @default.
- W1514675060 hasRelatedWork W2912173721 @default.
- W1514675060 hasRelatedWork W3036591508 @default.
- W1514675060 hasRelatedWork W3096769599 @default.
- W1514675060 hasRelatedWork W3124959132 @default.
- W1514675060 hasRelatedWork W3164642784 @default.
- W1514675060 isParatext "false" @default.
- W1514675060 isRetracted "false" @default.
- W1514675060 magId "1514675060" @default.
- W1514675060 workType "article" @default.