Abstract
With the wide application of mobile Internet techniques an location-based services (LBS), massive multimedia data with geo-tags has been generated and collected. In this paper, we investigate a novel type of spatial query problem, named reverse spatial visual top- $k$ query (RSVQ k ) that aims to retrieve a set of geo-images that have the query as one of the most relevant geo-images in both geographical proximity and visual similarity. Existing approaches for reverse top- $k$ queries are not suitable to address this problem because they cannot effectively process unstructured data, such as image. To this end, firstly we propose the definition of RSVQ k problem and introduce the similarity measurement. A novel hybrid index, named VR2-Tree is designed, which is a combination of visual representation of geo-image and R-Tree. Besides, an extension of VR2-Tree, called CVR2-Tree is introduced and then we discuss the calculation of lower/upper bound, and then propose the optimization technique via CVR2-Tree for further pruning. In addition, a search algorithm named RSVQ k algorithm is developed to support the efficient RSVQ k query. Comprehensive experiments are conducted on four geo-image datasets, and the results illustrate that our approach can address the RSVQ k problem effectively and efficiently.
Highlights
IntroductionWith the wide application of mobile Internet techniques and location-based services (LBS), massive multimedia data with geo-tags (geo-multimedia for short) has been generated and collected by smartphones and tablets with local sensors, and uploaded and stored on the Internet
With the wide application of mobile Internet techniques and location-based services (LBS), massive multimedia data with geo-tags has been generated and collected by smartphones and tablets with local sensors, and uploaded and stored on the Internet
We present a novel hybrid index, named VR2-Tree which is a combination of visual representations of geo-images and R-Tree
Summary
With the wide application of mobile Internet techniques and location-based services (LBS), massive multimedia data with geo-tags (geo-multimedia for short) has been generated and collected by smartphones and tablets with local sensors, and uploaded and stored on the Internet. Via sharing the geo-texts and geo-images uploaded by users Another LBS application is Foursquare, which helps users to share the places visited and find the best places nearby via geo-multimedia data. These geo-multimedia data is a fusion of multimedia content [1], [2] and geo-location information [3], which enables queries consider geographical proximity and multimedia content similarity simultaneously
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