Detecting Anomalies in Transaction Data: = Anomalieentdeckung in Transaktionsdaten
Gespeichert in:
1. Verfasser: | |
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Format: | Abschlussarbeit Buch |
Sprache: | English |
Veröffentlicht: |
Würzburg
2022
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Schlagworte: | |
Online-Zugang: | kostenfrei |
Beschreibung: | ix, 197 Seiten |
DOI: | 10.25972/OPUS-29856 |
Internformat
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Datensatz im Suchindex
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adam_text | |
adam_txt | |
any_adam_object | |
any_adam_object_boolean | |
author | Schlör, Daniel |
author_GND | (DE-588)1285304764 |
author_facet | Schlör, Daniel |
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author_sort | Schlör, Daniel |
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discipline | Informatik |
discipline_str_mv | Informatik |
doi_str_mv | 10.25972/OPUS-29856 |
format | Thesis Book |
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physical | ix, 197 Seiten |
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spelling | Schlör, Daniel Verfasser (DE-588)1285304764 aut Detecting Anomalies in Transaction Data = Anomalieentdeckung in Transaktionsdaten vorgelegt von Daniel Schlör Anomalieentdeckung in Transaktionsdaten Würzburg 2022 ix, 197 Seiten txt rdacontent n rdamedia nc rdacarrier Dissertation Julius-Maximilians-Universität Würzburg 2022 Zusammenfassung in deutscher und englischer Sprache Archivierung/Langzeitarchivierung gewährleistet DE-101 pdager 4\p Maschinelles Lernen (DE-588)4193754-5 gnd 5\p Datenanalyse (DE-588)4123037-1 gnd 6\p Neuronales Netz (DE-588)4226127-2 gnd 7\p Merkmalsextraktion (DE-588)4314440-8 gnd 8\p Datensicherung (DE-588)4011144-1 gnd 9\p Data Mining (DE-588)4428654-5 gnd 10\p Anomalieerkennung (DE-588)1042742219 gnd Fraud detection (DE-588)4113937-9 Hochschulschrift gnd-content Erscheint auch als Online-Ausgabe urn:nbn:de:bvb:20-opus-298569 doi:10.25972/OPUS-29856 https://doi.org/10.25972/OPUS-29856 Resolving-System kostenfrei Volltext 1\p aepkn 0,95047 20221227 DE-101 https://d-nb.info/provenance/plan#aepkn 2\p emasg 0,71588 20221227 DE-101 https://d-nb.info/provenance/plan#emasg 3\p npi 20221226 DE-101 https://d-nb.info/provenance/plan#npi 4\p emagnd 0,61808 20221227 DE-101 https://d-nb.info/provenance/plan#emagnd 5\p emagnd 0,11874 20221227 DE-101 https://d-nb.info/provenance/plan#emagnd 6\p emagnd 0,09060 20221227 DE-101 https://d-nb.info/provenance/plan#emagnd 7\p emagnd 0,07412 20221227 DE-101 https://d-nb.info/provenance/plan#emagnd 8\p emagnd 0,06512 20221227 DE-101 https://d-nb.info/provenance/plan#emagnd 9\p emagnd 0,05751 20221227 DE-101 https://d-nb.info/provenance/plan#emagnd 10\p emagnd 0,05351 20221227 DE-101 https://d-nb.info/provenance/plan#emagnd |
spellingShingle | Schlör, Daniel Detecting Anomalies in Transaction Data = Anomalieentdeckung in Transaktionsdaten 4\p Maschinelles Lernen (DE-588)4193754-5 gnd 5\p Datenanalyse (DE-588)4123037-1 gnd 6\p Neuronales Netz (DE-588)4226127-2 gnd 7\p Merkmalsextraktion (DE-588)4314440-8 gnd 8\p Datensicherung (DE-588)4011144-1 gnd 9\p Data Mining (DE-588)4428654-5 gnd 10\p Anomalieerkennung (DE-588)1042742219 gnd |
subject_GND | (DE-588)4193754-5 (DE-588)4123037-1 (DE-588)4226127-2 (DE-588)4314440-8 (DE-588)4011144-1 (DE-588)4428654-5 (DE-588)1042742219 (DE-588)4113937-9 |
title | Detecting Anomalies in Transaction Data = Anomalieentdeckung in Transaktionsdaten |
title_alt | Anomalieentdeckung in Transaktionsdaten |
title_auth | Detecting Anomalies in Transaction Data = Anomalieentdeckung in Transaktionsdaten |
title_exact_search | Detecting Anomalies in Transaction Data = Anomalieentdeckung in Transaktionsdaten |
title_exact_search_txtP | Detecting Anomalies in Transaction Data = Anomalieentdeckung in Transaktionsdaten |
title_full | Detecting Anomalies in Transaction Data = Anomalieentdeckung in Transaktionsdaten vorgelegt von Daniel Schlör |
title_fullStr | Detecting Anomalies in Transaction Data = Anomalieentdeckung in Transaktionsdaten vorgelegt von Daniel Schlör |
title_full_unstemmed | Detecting Anomalies in Transaction Data = Anomalieentdeckung in Transaktionsdaten vorgelegt von Daniel Schlör |
title_short | Detecting Anomalies in Transaction Data |
title_sort | detecting anomalies in transaction data anomalieentdeckung in transaktionsdaten |
title_sub | = Anomalieentdeckung in Transaktionsdaten |
topic | 4\p Maschinelles Lernen (DE-588)4193754-5 gnd 5\p Datenanalyse (DE-588)4123037-1 gnd 6\p Neuronales Netz (DE-588)4226127-2 gnd 7\p Merkmalsextraktion (DE-588)4314440-8 gnd 8\p Datensicherung (DE-588)4011144-1 gnd 9\p Data Mining (DE-588)4428654-5 gnd 10\p Anomalieerkennung (DE-588)1042742219 gnd |
topic_facet | Maschinelles Lernen Datenanalyse Neuronales Netz Merkmalsextraktion Datensicherung Data Mining Anomalieerkennung Hochschulschrift |
url | https://doi.org/10.25972/OPUS-29856 |
work_keys_str_mv | AT schlordaniel detectinganomaliesintransactiondataanomalieentdeckungintransaktionsdaten AT schlordaniel anomalieentdeckungintransaktionsdaten |