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Average Case analyses of List Update Algorithms, with Applications to Data COmpression

机译:列表更新算法的平均案例分析及其在数据压缩中的应用

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We study the performance of the Timestamp(0) algorithm for self-organizing sequential search on discrete memoryless sources. We demonstrate that TS(0) is better than MOve-to-front on such sources, and determine performance ratios for TS(0) against the optimal offline and static adversaries in this situation. Previous work on such sources compared online algorithms only to static adversaries. One practical motivation for our work is the sue of the Move-to-front heuristic in various compression algorithms. Our theoretical results suggest that in many cases uning TS(0) in place of Move-to-front in schemes that use the latter should improve compression. Tests on a standard corpus of documents demonstrate that TS(0) leads in fact to improved compression.
机译:我们研究了Timestamp(0)算法在离散无记忆源上自组织顺序搜索的性能。我们证明TS(0)在此类来源上要优于前移,并确定TS(0)在这种情况下相对于最佳离线和静态对手的性能比。以前在此类资源上的工作仅将在线算法与静态对手进行了比较。我们工作的一项实际动机是在各种压缩算法中诉诸于“向前移动”启发式方法。我们的理论结果表明,在许多情况下,使用TS(0)代替使用前移方案的前移应可改善压缩率。对标准文档集的测试表明,TS(0)实际上导致压缩率的提高。

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