Authors:
Semih Utku
and
Canan Eren Atay
Affiliation:
Dokuz Eylul University, Turkey
Keyword(s):
A Mobile Location-Aware Recommendation System
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Data Analytics
;
Data Engineering
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Software Development
;
Symbolic Systems
Abstract:
Improvements in mobile technology provide greater personal information accessibility, data incorporation, and public resources accessibility, “anytime, anywhere”. Smartphones are not only devices that make phone calls, but have also become a gateway to the Internet. Mobile devices offer the capabilities of usage flexibility, mobility, fast wireless communication, and location-awareness. Location is determined by GPS satellite tracking, position relative to GSM base stations, and the device's media access control. Similarly, usage of social networks is increasing steadily. Widespread usage of social networks introduces new requirements of Internet application. Users of such networks share their ideas and interests, as well as the activities they plan to attend. In addition, they follow other users’ information and shape their planned activities accordingly. In this study, an intelligent context-aware system is described. In this field, context-awareness is a mobile paradigm in which a
pplications can discover and take advantage of contextual information, such as user location, nearby people and devices, and user activity. This system provides an activity list that users plan to attend. Our recommender system creates results based on data mining techniques, by using personal identification data and user activities. The recommender system brings novel methodology to the activity-decision process by utilizing the right location and real-time information.
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