Benefit from Automated Product Recommendations at kdmz
Authors
Author (Corporation)
Publication date
06.08.2009
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Type
04B - Conference paper
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Parent work
Proceedings of the Fifteenth Americas Conference on Information Systems (AMCIS)
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Place of publication / Event location
San Francisco
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Abstract
There are a number of recommender systems with different characteristics (Nageswara Rao and Talwar 2008). For a company it is not easy to select the right system. For the introduction of a recommender system is decisive, what kind of data exists and how suitable this data is for calculating recommendations. The question must be answered which algorithm calculates the best recommendations with these data. Afterwards the recommender system has to be developed and integrated into the existing systems (e. g. e-shop). This paper describes the case where a recommender system was introduced successfully into an existing system. For the description of this case the eXperience Methodology was used (Schubert and Wölfle 2007). According to this methodology the company is described first, and then some views onto the final solution, the project and development and to conclude the experiences which were made with the solution.
Keywords
Subject (DDC)
330 - Wirtschaft
005 - Computer Programmierung, Programme und Daten
005 - Computer Programmierung, Programme und Daten
Event
Fifteenth Americas Conference on Information Systems (AMCIS)
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Language
English
Created during FHNW affiliation
Unknown
Strategic action fields FHNW
Publication status
Published
Review
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Open access category
License
Citation
QUADE, Michael H., 2009. Benefit from Automated Product Recommendations at kdmz. In: Proceedings of the Fifteenth Americas Conference on Information Systems (AMCIS). San Francisco. 6 August 2009. Verfügbar unter: https://doi.org/10.26041/fhnw-3108