By Topic

A mobile product recommendation system interacting with tagged products

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
von Reischach, F. ; Auto-ID Labs., ETH Zurich, Zurich ; Guinard, D. ; Michahelles, F. ; Fleisch, E.

This paper presents a concept that enables consumers to access and share product recommendations using their mobile phone. Based on a review of current product recommendation mechanisms it devises a concept called APriori. APriori leverages the potential of auto-ID-enabled mobile phones (barcode/RFID) to receive and submit product ratings. Since mobile users cannot be expected to have the patience and time to compose text-based reviews on mobile phones, we introduce a new rating concept that allows users to generate new rating criteria. The concept is tailored to the limited attention and input options of mobile users in real-world environment. This work describes the architecture, implementation, and evaluation of APriori. For an evaluation we have taken the approach of interviewing 26 users in the frames of a formative user study, with the goal to further improve the system for an application in the real world. In addition, the paper discusses open issues regarding community-based product recommendations on mobile phones and proposes solutions.

Published in:

Pervasive Computing and Communications, 2009. PerCom 2009. IEEE International Conference on

Date of Conference:

9-13 March 2009