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.
%0 Journal Article
%1 von2009mobile
%A von Reischach, F.
%A Guinard, D.
%A Michahelles, F.
%A Fleisch, E.
%B IEEE Conference on Pervasive Computing and Communications (PerCom 2009)
%D 2009
%K Auto-ID Barcode Mobile_Computing Mobile_Phone Product_Rating Product_Recommender_System RFID Recommender_System Tagged_Product
%T A mobile product recommendation system interacting with tagged products
%U http://scholar.google.de/scholar.bib?q=info:FvCPfZn2tqgJ:scholar.google.com/&output=citation&hl=de&as_sdt=2000&ct=citation&cd=0
%X 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.
@article{von2009mobile,
abstract = {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.},
added-at = {2010-01-30T10:09:52.000+0100},
author = {von Reischach, F. and Guinard, D. and Michahelles, F. and Fleisch, E.},
biburl = {https://www.bibsonomy.org/bibtex/2ce23517f633fba6a728c7f8b6772a9a3/altmann},
booktitle = {IEEE Conference on Pervasive Computing and Communications (PerCom 2009)},
interhash = {baeba9e13c6e92d2c96b58f787668c40},
intrahash = {ce23517f633fba6a728c7f8b6772a9a3},
keywords = {Auto-ID Barcode Mobile_Computing Mobile_Phone Product_Rating Product_Recommender_System RFID Recommender_System Tagged_Product},
timestamp = {2010-01-30T10:09:53.000+0100},
title = {{A mobile product recommendation system interacting with tagged products}},
url = {http://scholar.google.de/scholar.bib?q=info:FvCPfZn2tqgJ:scholar.google.com/&output=citation&hl=de&as_sdt=2000&ct=citation&cd=0},
year = 2009
}