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Information Extraction Engine for Sentiment-Topic Matching in Product Intelligence Applications

  • Cornelia FernerEmail author
  • Werner Pomwenger
  • Stefan Wegenkittl
  • Martin Schnöll
  • Veronika Haaf
  • Arnold Keller
Conference paper

Zusammenfassung

Produktbewertungen sind eine wertvolle Informationsquelle sowohl für Unternehmen als auch für Kunden. Während Unternehmen diese Informationen dazu nutzen, ihre Produkte zu verbessern, benötigen Kunden sie als Unterstützung für die Entscheidungsfindung. Mit Bewertungen, Kommentaren und zusätzlichen Informationen versuchen viele Onlineshops potenzielle Kunden dazu zu animieren, auf ihrer Seite einzukaufen. Allerdings mangelt es aktuellen Online-Bewertungen an einer Kurzzusammenfassung, inwieweit bestimmte Produktbestandteile den Kundenwünschen entsprechen, wodurch der Produktvergleich erschwert wird. Daher haben wir ein Produktinformationswerkzeug entwickelt, dass gängige Technologien in einer Engine maschineller Sprachverarbeitung vereint. Die Engine ist in der Lage produktbezogene Online-Daten zu sammeln und zu sichern, Metadaten auszulesen und Meinungen. Die Engine wird auf technische Online-Produktbewertungen zur Stimmungsanalyse auf Bestandteilsebene angewendet. Der vollautomatisierte Prozess durchsucht das Internet nach Expertenbewertungen, die sich auf Produktbestandteile beziehen, und aggregiert die Stimmungswerte der Bewertungen.

Schlüsselwörter

information extraction topic detection sentiment analysis natural language processing product intelligence 

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Copyright information

© Springer Fachmedien Wiesbaden GmbH 2017

Authors and Affiliations

  • Cornelia Ferner
    • 1
    Email author
  • Werner Pomwenger
    • 1
  • Stefan Wegenkittl
    • 1
  • Martin Schnöll
    • 2
  • Veronika Haaf
    • 2
  • Arnold Keller
    • 2
  1. 1.Salzburg University of Applied SciencesSalzburgÖsterreich
  2. 2.Fact AI KGSalzburgÖsterreich

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