Matching Innovation Descriptions with Organization Profiles
Kein Vorschaubild vorhanden
Autor:innen
Autor:in (Körperschaft)
Publikationsdatum
2017
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
Open Innovation platforms are becoming increasingly common to share knowledge. Organizations searching for innovative ideas and providers of innovations have to sign up on these platforms to participate in the market. Establishing a match between the two parties can be challenging and even a matter of luck. This thesis proposes a practitioner-oriented take on how this process can partially be automatized by making use of techniques from the area of Natural Language Processing and Information Retrieval. A prototypical implementation was built in the Java programming language to validate the premise that such a system can be built and that it yields reasonable results. The document compares and evaluates methods to extract relevant keywords and other information from the websites of organizations as well as from textual innovation descriptions. The resulting organization and innovation proles can then be matched with the help of an enterprise search engine. The most promising methods were evaluated using the prototype. A qualitative review highlights the strenghts and weaknesses of each approach. It is shown that keywords can indeed be extracted from websites and innovation descriptions, albeit with mixed outcomes. While the results of certain methods such as Latent Dirichlet Allocation were rather underwhelming, other approaches such as keyword assignment with a controlled vocabulary yielded keyword candidates comparable to humans.
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
Zukunftsfelder FHNW
Publikationsstatus
Begutachtung
Open Access-Status
Lizenz
Zitation
STÖCKLI, Matthias, 2017. Matching Innovation Descriptions with Organization Profiles. Olten: Hochschule für Wirtschaft FHNW. Verfügbar unter: https://irf.fhnw.ch/handle/11654/39973