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dc.contributor.authorChang, Maiga
dc.date.accessioned2014-01-16T20:07:55Z
dc.date.available2014-01-16T20:07:55Z
dc.date.issued2014-01-16T20:07:55Z
dc.identifier.urihttp://hdl.handle.net/2149/3415
dc.descriptionThe earlier precedent research had designed an algorithm which is capable of finding a user’s wandering behaviour pattern and further comparing the extracted pattern with other users’. With the similarity measurement, the precedent research can recommend a user next stop(s) that he or she might be interested according to his or her past wandering behaviours. This research further developed an Android mobile app which integrates different positioning technologies such as QR Code and GPS and the proposed algorithm to provide users a personalized service which can be used in a variety of application domains such like tourism, field trips, and mobile learning. Some participants of the presentation argued that the system should record users’ wandering behaviours in local time instead of the time on their mobile devices. The argument is thoughtful and useful. The next stop of this research will be categorizing users’ wandering patterns based on time and event as well as point of interests. This research is also looking for partners to use the mobile app and to give the research team the feedback in terms of its usability and user perceptions; looking for partners to use the next stop recommender algorithm or app in their existing and prospective research and/or system/app.en
dc.description.abstractUser wandering behaviours may involve many location visits in different order. The research team has proposed an algorithm which can provide users recommendation for their next visit according to the behaviour pattern similarity amongst users and the connections amongst locations. In order to test the effectiveness of proposed algorithm the research team develops a mobile app – Next Stop Recommender – for Android platform. This paper focuses on the app itself and discusses the potential use of the app and the directions for the algorithm enhancement.en
dc.language.isoenen
dc.relation.ispartofseries92.927.G1445;
dc.subjectAlgorithm enhancementen
dc.subjectUser wandering behavioursen
dc.titleNext Stop Recommenderen
dc.typePresentationen


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