Ontology-based recommender system satisfying application requirements

Pacar, Maria, 2019

Art der Arbeit Master Thesis
Auftraggebende
Betreuende Dozierende Hinkelmann, Knut
Keywords
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Companies are increasingly recognizing the potential of the recommendation system. Various filter methods for recommendation systems have been identified in the literature. These are collaborative filtering (e.g., customers who bought product A, also product B),content-based filtering (e.g., you bought a printer, you may also need ink) or knowledge-based filtering (e.g., we know you like skirts: do you prefer the red or the blue skirt?). Two or more methods can be combined into so-called hybrid systems that try to combine the best aspects of each system. Another new trend is chatbots, as they can offer a personal and fast service to the customer. The combination of both technologies makes it easier for companies to communicate with their customers. The goal is for the customer to come back. However, current solutions do not focus on the alignment between the application view and the technical view; customers need to have a lot of expertise....
Studiengang: Business Information Systems (Master)
Vertraulichkeit: vertraulich
Art der Arbeit
Master Thesis
Autorinnen und Autoren
Pacar, Maria
Betreuende Dozierende
Hinkelmann, Knut
Publikationsjahr
2019
Sprache der Arbeit
Englisch
Vertraulichkeit
vertraulich
Studiengang
Business Information Systems (Master)
Standort Studiengang
Olten