Use of automatic speech recognition for invoice related activity recording processes in Swiss healthcare
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Autor:innen
Autor:in (Körperschaft)
Publikationsdatum
2018
Typ der Arbeit
Master
Studiengang
Sammlung
Typ
11 - Studentische Arbeit
Herausgeber:innen
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
Themenheft
DOI der Originalpublikation
Link
Reihe / Serie
Reihennummer
Jahrgang / Band
Ausgabe / Nummer
Seiten / Dauer
Patentnummer
Verlag / Herausgebende Institution
Hochschule für Wirtschaft FHNW
Verlagsort / Veranstaltungsort
Olten
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
Even the smallest enterprise has to manage so much information and documents, that a system for arranging these things is needed; even if it is a small binder. Now when we think about the amount of information which today exists in a company, we have surely to say, that information and knowledge management is not done by only one binder – the companies nowadays need something more sophisticated. What companies nowadays need is information about information – metadata. If metadata is available, then the finding and filing process can be dramatically improved. But if the metadata is not available, it needs to be created – and this has to be done in most of the cases by hand. Would it not be great to have an automatic approach? This thesis introduces an approach for creating metadata in an automatic way based on rules and a formal description of an enterprise. We often hear the statement that a company has the information available – ‚We have the information in our systems.‛ But it is the question how the information is available. The Linked Enterprise Models and Objects (LEMO) approach gives the possibility to formalise the information in an enterprise. And not only the infor-mation, LEMO tries to make the relationships / links between different enterprise objects, documents, people, customers, money, almost everything in an enterprise explicit and machine process able using an ontology called enterprise model ontology (EMO). This EMO can be seen as context description of an entire enterprise. And this context can be used to create metadata using rules....
Schlagwörter
Fachgebiet (DDC)
330 - Wirtschaft
Veranstaltung
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
Enddatum der Konferenz
Datum der letzten Prüfung
ISBN
ISSN
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Publikationsstatus
Begutachtung
Open Access-Status
Lizenz
Zitation
MAURON, Severin, 2018. Use of automatic speech recognition for invoice related activity recording processes in Swiss healthcare. Olten: Hochschule für Wirtschaft FHNW. Verfügbar unter: https://irf.fhnw.ch/handle/11654/39876