Road-based travel recommendation using geo-tagged images

Sun, Yeran; Fan, Hongchao; Bakillah, Mohamed; Zipf, Alexander

doi:10.1016/j.compenvurbsys.2013.07.006

Cited by 121 publications

(101 citation statements)

References 36 publications

(35 reference statements)

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“…Zheng et al investigated tourist's movement patterns in relation to the regions of attractions and the topological characteristics of travel routes visited by different tourists [16]. Sun et al built a recommendation system that provides users with the optimal travel routes, of which the basic unit is the separate road segment instead of the GPS trajectory segment [17]. Simply put, those exploratory investigations are making Flickr photograph data the most promising data source for tourism study in academic society.…”

Section: Introductionmentioning

confidence: 99%

Quantifying Tourist Behavior Patterns by Travel Motifs and Geo-Tagged Photos from Flickr

Liu

et al. 2017

IJGI

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Abstract:With millions of people traveling to unfamiliar cities to spend holidays, travel recommendation becomes necessary to assist tourists in planning their trips more efficiently. Serving as a prerequisite to travel recommender systems, understanding tourist behavior patterns is therefore of great importance. Recently, geo-tagged photos on social media platforms like Flickr have provided a rich data source that captures location histories of tourists and reflects their preferences. This article utilizes geo-tagged photos from Flickr to extract trajectories of tourists and then extends the concept of motifs from topological spaces, to temporal spaces and to semantic spaces, for detecting tourist mobility patterns. By representing trajectories in terms of three distinct types of travel motif and further using them to measure user similarity, typical tourist travel behavior patterns associated with distinct sightseeing tastes/preferences are identified and analyzed for tourism recommendation. Our empirical results confirm that the proposed analytical framework is effective to uncover meaningful tourist behavior patterns.

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Section: Introductionmentioning

confidence: 99%

Quantifying Tourist Behavior Patterns by Travel Motifs and Geo-Tagged Photos from Flickr

Liu

et al. 2017

IJGI

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“…This bottom-up process of collecting individuals' contributions has resulted in shaping big (geo)data, which has leveraged new applications such as indoor mapping (Goetz & Zipf, 2010), routing applications (Bakillah et al, 2014), tourism recommendations (Sun, Fan, Bakillah, & Zipf, 2013), and environmental monitoring (Fritz et al, 2012;Jokar Arsanjani & Vaz, 2015). Although the question on how to attract users and how to keep them active in the crowdsourcing activities is yet to be addressed, OSM has shown its continuing success in attracting more than 2.7 million users.…”

Section: Conclusion and Recommendationsmentioning

confidence: 99%

On the Contribution of Volunteered Geographic Information to Land Monitoring Efforts

Arsanjani

Fonte

2016

European Handbook of Crowdsourced Geographic Information

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Land-related inventories are important sources of geoinformation for environmentalists, researchers, policy-makers, practitioners, and ecologists. Traditionally, a considerable amount of energy, time, and money have been dedicated to map global/regional/local land use datasets. While remote sensing images and techniques along with field surveying have been the main sources of data for determining land use features, field measurements of ground truth have always amplified the required time and money, as well as information credibility. Nowadays, volunteered geographic information (VGI) has shown its great contributions to different scientific disciplines. This was made possible thanks to Web 2.0 technologies and GPS-enabled devices, which have advanced citizens knowledge-based projects and made them user-friendly for volunteered citizens to collect and share their knowledge about geographical objects. OpenStreetMap as one of those leading VGI projects has shown its great potential for collecting and providing land use information. The collaboratively collected 270 European Handbook of Crowdsourced Geographic Information land use features from diverse citizens could greatly back up the challenging element of land use mapping, which is in-field data gathering. Hence, in this literature we will look at the completeness, thematic accuracy and fitness for use of OpenStreetMap features for land mapping purposes over European countries. The empirical findings reveal that the degree of completeness varies widely ranging from 2% to 96% and overall and per-class thematic accuracies goes up to 80% and 96%, respectively compared to the European GMESUA datasets. Furthermore, more than 50% of land use features of eight European countries are mapped. This messages that the harnessing citizens' knowledge can play a great role in land mapping as an alternative and complementary data source.

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“…Hao et al [35] presented Travelscope, a system that created virtual tours by mining Flickr data. Sun et al [36] clustered images spatially, identified landmarks within them and ranked them based on their popularity. They aimed to recommend to the user minimum distances with maximum tourism popularity.…”

Section: ) Recommendation Systemsmentioning

confidence: 99%

An Overview of Flickr Challenges and Research Opportunities

Spyrou

Mylonas

2014

2014 9th International Workshop on Semantic and Social Media Adaptation and Personalization

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Abstract-It is rather true that nowadays diversity and a potential for growth characterize the field of popular social networks like Flickr. Based on this observation, we provide herein a brief overview of the basic characteristics, challenges and research opportunities of the latter. Some historical facts of its origin are presented, followed by a review of its digital photo sharing and tagging capabilities, focusing on the most popular related research fields, like travel applications, knowledge extraction and human activity tracking. Throughout the paper the status of current research and directions for future research are highlighted in an effort to provide useful information to fellow researchers.

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Road-based travel recommendation using geo-tagged images

Cited by 121 publications

References 36 publications

Quantifying Tourist Behavior Patterns by Travel Motifs and Geo-Tagged Photos from Flickr

Quantifying Tourist Behavior Patterns by Travel Motifs and Geo-Tagged Photos from Flickr

On the Contribution of Volunteered Geographic Information to Land Monitoring Efforts

An Overview of Flickr Challenges and Research Opportunities

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