Spatial concepts, geometric data models, and geometric data structures
Computers & Geosciences - Special issue on GIS design models
A comparison of methods for representing topological relationships
Information Sciences—Applications: An International Journal
Information Sciences: an International Journal
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
A robust framework for content-based retrieval by spatial similarity in image databases
ACM Transactions on Information Systems (TOIS)
A Small Set of Formal Topological Relationships Suitable for End-User Interaction
SSD '93 Proceedings of the Third International Symposium on Advances in Spatial Databases
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
Indexing and ranking in Geo-IR systems
Proceedings of the 2005 workshop on Geographic information retrieval
Improvement of PageRank for Focused Crawler
SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02
A Relation-Based Page Rank Algorithm for Semantic Web Search Engines
IEEE Transactions on Knowledge and Data Engineering
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
To Construct Implicit Link Structure by Using Frequent Sequence Miner (FS-Miner)
ICCET '09 Proceedings of the 2009 International Conference on Computer Engineering and Technology - Volume 01
Index Design for Dynamic Personalized PageRank
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Hi-index | 0.00 |
In recent years, Remote Sensing Images (RS-Images) are widely recognized as an essential geospatial data due to their superior ability to offer abundant and instantaneous ground truth information. One of the active RS-Image approaches is the RS-Image recommendation from the Internet for meeting the user's queried Area-of-Interest (AOI). Although a number of studies on RS-Image ranking and recommendation have been proposed, most of them only consider the spatial distance between RS-Image and AOI. It is inappropriate since both of the RS-Image and AOI not only have the spatial information but also the cover range information. In this paper, we propose a novel framework named Location-based rs-Image Finding Engine (LIFE) to rank and recommend a series of relevant RS-Images to users according to the user-specific AOI. In LIFE, we first propose a cluster-based RS-Image index structure to efficiently maintain the large amount of RS-Images. Then, two quantitative indicators named Available Space (AS) and Image Extension (IE) are proposed to measure the Extensibility and Centrality between RS-Image and AOI, respectively. To our best knowledge, this is the first work on RS-Image recommendation that considers the issues of extensibility and centrality simultaneously. Through comprehensive experimental evaluations, the experiment result shows that both indicators have their own distinguished ranking behaviors and are able to successfully recommend meaningful RS-Image results. Besides, the experimental results show that the proposed LIFE framework outperforms the state-of-the-art approach Hausdorff in terms of Precision, Recall and Normalized Discounted Cumulative Gain (NDCG).