A fuzzy data mining approach for remote sensing image recommendation

Eric Hsueh Chan Lu, Jung Hong Hong, Zeal Li Tse Su, Chun Hao Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Nowadays research on Remote Sensing Images (RS-Images) ranking and recommendation for meeting the user-specific Area-Of-Interest (AOI) has received a log of attentions due to a wide range of potential applications. In this paper, we propose a novel approach named Fuzzy rs-Image Recommender (FIR) to rank and recommend relevant RS-Images according to the queried AOI. In FIR, we first propose two features named Available Space (AS) and Image Extension (IE) as two indicators to represent the relationships between AOI and RS-Image. Then, we mine the fuzzy association rules between the proposed indicators and user rating score. Finally, we propose two fuzzy inference strategies named FIR with Weightarea (FIRarea) and FIR with Weightall(FIR all) to rank and recommend the relevant RS-Images to users. To our best knowledge, this is the first work on RS-Image recommendation that considers the issues of feature extraction and fuzzy rule mining, simultaneously. Through comprehensive experimental evaluations, the results show that the proposed FIR approach outperforms the state-of-the-art approach Hausdorff in terms of Normalized Discounted Cumulative Gain (NDCG).

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE International Conference on Granular Computing, GrC 2013
PublisherIEEE Computer Society
Pages213-218
Number of pages6
ISBN (Print)9781479912810
DOIs
Publication statusPublished - 2013 Jan 1
Event2013 IEEE International Conference on Granular Computing, GrC 2013 - Beijing, China
Duration: 2013 Dec 132013 Dec 15

Publication series

NameProceedings - 2013 IEEE International Conference on Granular Computing, GrC 2013

Other

Other2013 IEEE International Conference on Granular Computing, GrC 2013
CountryChina
CityBeijing
Period13-12-1313-12-15

All Science Journal Classification (ASJC) codes

  • Software

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