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Titlebook: Web-Age Information Management; WAIM 2013 Internatio Yunjun Gao,Kyuseok Shim,Shaojie Qiao Conference proceedings 2013 Springer-Verlag Berli

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Incremental Truth Discovery for Information from Multiple Data Sourcesive for different update situations by considering concept drift in learning process. Our based model can treat entities inconsistently for a source also. These make truth finding more effective without repetitive computation.
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DL-Dedupe: Dual-Level Deduplication Scheme for Flash-Based SSDssumption, the limited write endurance of flash and the reliability problem hold back the footsteps of SSD popularization. We propose DL-Dedupe, a dual-level deduplication scheme for flash-based SSDs to reduce the amount of data written to flash memory and enhance the storage capacity at the same tim
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SFCM: A SSD-Friendly Cache Management Policy for Hybrid Storage Systemsompared with conventional magnetic disk, SSD can provide higher access bandwidth and lower access latency. However, it will not completely replace the disk as the secondary storage in the short run due to its inherent properties such as asymmetric read/write, high price of per gigabyte etc. Integrat
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An Efficient Strategy of Building Distributed Index Based on Luceneal of large amount of data becomes more and more necessary. In this paper, we propose an efficient and smooth strategy of building distributed index for large amount of text. In order to improve memory usage and less manual intervention, the proposed strategy uses dynamic threshold setting other tha
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Adaptive Sequential Prefetching for Multiple Streamsial prefetching is widely used in modern storage system. Most of them always ignore the impact of diversified access rate of concurrent streams. However the concurrent streams with diversified access rate will introduce several problems. The streams with fast access rate may evict the cache blocks o
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Incremental Truth Discovery for Information from Multiple Data Sourceslgorithm more practical, we present an incremental strategy in multisource integration using boosting like ensemble classifier. Our algorithm is adaptive for different update situations by considering concept drift in learning process. Our based model can treat entities inconsistently for a source a
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