Institut für Wirtschaftsinformatik
Dauerhafte URI für die Sammlunghttps://irf.fhnw.ch/handle/11654/66
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3 Ergebnisse
Ergebnisse nach Hochschule und Institut
Publikation How to support customer segmentation with useful cluster descriptions(Springer, 2015) Witschel, Hans Friedrich; Loo, Simon; Riesen, Kaspar; Perner, PetraCustomer or market segmentation is an important instrument for the optimisation of marketing strategies and product portfolios. Clustering is a popular data mining technique used to support such segmentation – it groups customers into segments that share certain demographic or behavioural characteristics. In this research, we explore several automatic approaches which support an important task that starts after the actual clustering, namely capturing and labeling the “essence” of segments. We conducted an empirical study by implementing several of these approaches, applying them to a data set of customer representations and studying the way our study participants interacted with the resulting cluster representations. Major goal of the present paper is to find out which approaches exhibit the greatest ease of understanding on the one hand and which of them lead to the most correct interpretation of cluster essence on the other hand. Our results indicate that using a learned decision tree model as a cluster representation provides both good ease of understanding and correctness of drawn conclusions.04B - Beitrag KonferenzschriftPublikation Smart unterschrieben(Swiss Professional Media, 01/2017) Riesen, Kaspar; Lorgé, ChristineSKETCH-ID: Eine einzigartige Software erkennt die persönliche Unterschrift fälschungssicher auf mobilen Geräten. Allseits unbeliebte Passwörter könnten damit schon bald der Vergangenheit angehören und Vertragsabschlüsse komplett digital abgewickelt werden. Eine Firma aus Bern hat zusammen mit der Fachhochschule Nordwestschweiz den Algorithmus entwickelt.01B - Beitrag in Magazin oder ZeitungPublikation A Graph-Based Recommender for Enhancing the Assortment of Web Shops(2015) Riesen, Kaspar; Witschel, Hans Friedrich; Galliè, EmidioIn this work, we consider a situation where multiple Providers (competitors) serve a common market, using a common infrastructure of sales channels. More speci cally, we focus on multiple web shops that are run by the same web shop platform provider. Our goal is to recommend new items to complement the assortment of a provider, based on user behaviour in the other shops of the same platform. For this new problem, we propose to capture information on how items sell together in a shared product co-occurrence graph. We then adapt known graph-based recommenders to the problem. Further criteria for ranking recommended items are derived as part of a case study conducted in the context of IT web shops. They are combined with the scores of the graph recommenders in a nal ranking function. We evaluate this function with data from our case study context and based on judgments of one shop owner. Our results show that a good ranking can be achieved, reflecting the needs of the shop owner.04B - Beitrag Konferenzschrift