Recommending personalized scenic itinerarywith geo-tagged photos

Tai, Chih Hua; Yang, De-Nian; Lin, Lung Tsai; Chen, Ming-Syan

doi:10.1109/icme.2008.4607658

Cited by 4 publications

(1 citation statement)

References 19 publications

(10 reference statements)

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“…Through postprocessing, the raw GPS can be turned into a more usable form, such as routable road map [3]. Regarding travel and tourism applications, GPS data have been used to find locations of interest [2], integrated into a mobile tour guide [19,20,22], and combined with other resources such as geo-tagged photographs [21]. In GeoLife [29,32,36], many GPS-related applications and scenarios are introduced.…”

Section: Itinerary Recommendationmentioning

confidence: 99%

Social itinerary recommendation from user-generated digital trails

Yoon

Zheng

Xie

et al. 2011

Pers Ubiquit Comput

107

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Planning travel to unfamiliar regions is a difficult task for novice travelers. The burden can be eased if the resident of the area offers to help. In this paper, we propose a social itinerary recommendation by learning from multiple user-generated digital trails, such as GPS trajectories of residents and travel experts. In order to recommend satisfying itinerary to users, we present an itinerary model in terms of attributes extracted from usergenerated GPS trajectories. On top of this itinerary model, we present a social itinerary recommendation framework to find and rank itinerary candidates. We evaluated the efficiency of our recommendation method against baseline algorithms with a large set of user-generated GPS trajectories collected from Beijing, China. First, systematically generated user queries are used to compare the recommendation performance in the algorithmic level. Second, a user study involving current residents of Beijing is conducted to compare user perception and satisfaction on the recommended itinerary. Third, we compare mobile-only approach with Mobile?Cloud architecture for practical mobile recommender deployment. Lastly, we discuss personalization and adaptation factors in social itinerary recommendation throughout the paper.

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