Individualising M-Commerce Services by Semantic User Situation Modelling

Figge, Stefan; Albers, Andreas

doi:10.1007/3-7908-1624-8_83

Cited by 2 publications

(1 citation statement)

References 9 publications

(6 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The second stage is about the problem identification. The introduction already points out that the information overflow from a customer perspective [20] and the sales approach fi-om an advertiser perspective [9] are still not optimized fields by research. By using adaptive customer profiles, a reduction of search costs both on the customer and advertiser side can lead to differentiation and separation in the mobile commerce against the competition.…”

Section: Research Approachmentioning

confidence: 99%

Adaptive Customer Profiles For Context Aware Services in a Mobile Environment

Radmacher¹

IFIP — The International Federation for Information Processing

View full text Add to dashboard Cite

Mobile data communication generated 10 percent of the overall data revenue in Germany and between 2-3 percent worldwide [29] in 2004. This development is contradictory compared to the high investment (91.5 billion €) in networks and licenses that supported the UMTS infrastructure and thereby the mobile internet. An advertised-based revenue model [10] addresses an opportunity to increase the mobile data communication. Mobile customers and advertisers are matched based on the customer's current situation (location, time and interests). Precise customer profiles, as a requirement to overcome the information overflow, and to enable a multilateral economically reasonable matching are indispensable but the profile's quality is not given in reality. Without precise customer profiles there is no matching. With situation adaptive customer profiles the profile's quality is increasing. Its design, realization and integration into the mobile operator's infrastructure are the aim of this paper.

show abstract

Section: Research Approachmentioning

confidence: 99%