NDLI: Context-aware POI recommendations in an automotive scenario using multi-criteria decision making methods

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Context-aware POI recommendations in an automotive scenario using multi-criteria decision making methods

Content Provider	ACM Digital Library
Author	Neufeld, Eugen Prinz, Vivian Bader, Roland Woerndl, Wolfgang
Abstract	Recommender systems are commonly used for recommending items such as products, restaurants or other points-of-interest (POI). In our automotive scenario, the driver of a car gets recommendations for gas stations. Thereby, item attributes such as price or location are important, but also context data such as the current time, location or gas level of the car when requesting the recommendation. Our approach is based on Multi-Criteria Decision Making (MCDM) methods to calculate scores on several dimensions. We used utility functions modeling the importance of different route context elements which were derived from a preliminary user study, among other information. In addition, our system performs contextual pre- and post-filtering to reduce the number of considered items. The evaluation showed that our approach produced reasonably good results in comparison with the assessment of users in a second study.
Starting Page	23
Ending Page	30
Page Count	8
File Format	PDF
ISBN	9781450306256
DOI	10.1145/1961634.1961640
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-02-13
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Context Multi-criteria decision making Points-of-interest recommendations Recommender systems
Content Type	Text
Resource Type	Article

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