Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
On Robust Image Spam Filtering Via Comprehensive Visual Modeling, Jialie Shen, Deng, Robert H., Zhiyong Cheng, Liqiang Nie, Shuicheng Yan
On Robust Image Spam Filtering Via Comprehensive Visual Modeling, Jialie Shen, Deng, Robert H., Zhiyong Cheng, Liqiang Nie, Shuicheng Yan
Research Collection School Of Computing and Information Systems
The Internet has brought about fundamental changes in the way peoples generate and exchange media information. Over the last decade, unsolicited message images (image spams) have become one of the most serious problems for Internet service providers (ISPs), business firms and general end users. In this paper, we report a novel system called RoBoTs (Robust BoosTrap based spam detector) to support accurate and robust image spam filtering. The system is developed based on multiple visual properties extracted from different levels of granularity, aiming to capture more discriminative contents for effective spam image identification. In addition, a resampling based learning framework …
On Processing Reverse K-Skyband And Ranked Reverse Skyline Queries, Yunjun Gao, Qing Liu, Baihua Zheng, Mou Li, Gang Chen, Qing Li
On Processing Reverse K-Skyband And Ranked Reverse Skyline Queries, Yunjun Gao, Qing Liu, Baihua Zheng, Mou Li, Gang Chen, Qing Li
Research Collection School Of Computing and Information Systems
In this paper, for the first time, we identify and solve the problem of efficient reverse k-skyband (RkSB) query processing. Given a set P of multi-dimensional points and a query point q, an RkSB query returns all the points in P whose dynamic k-skyband contains q. We formalize RkSB retrieval, and then propose five algorithms for computing the RkSB of an arbitrary query point efficiently. Our methods utilize a conventional data-partitioning index (e.g., R-tree) on the dataset, and employ pre-computation, reuse and pruning techniques to boost the query efficiency. In addition, we extend our solutions to tackle an interesting variant …