%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 }