A comparison study on algorithms for incremental update of frequent sequences

Minghua Zhang, B. Kao, Chi Lap Yip
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引用次数: 12

Abstract

The problem of mining frequent sequences is to extract frequently occurring subsequences in a sequence database. Algorithms on this mining problem include GSP, MFS, and SPADE. The problem of incremental update of frequent sequences is to keep track of the set of frequent sequences as the underlying database changes. Previous studies have extended the traditional algorithms to efficiently solve the update problem. These incremental algorithms include ISM, GSP+ and MFS+. Each incremental algorithm has its own characteristics and they have been studied and evaluated separately under different scenarios. This paper presents a comprehensive study on the relative performance of the incremental algorithms as well as their non-incremental counterparts. Our goal is to provide guidelines on the choice of an algorithm for solving the incremental update problem given the various characteristics of a sequence database.
频繁序列增量更新算法的比较研究
频繁序列挖掘的问题是提取序列数据库中频繁出现的子序列。该问题的挖掘算法包括GSP、MFS和SPADE。频繁序列增量更新的问题是在底层数据库发生变化时跟踪频繁序列集。以往的研究对传统算法进行了扩展,以有效地解决更新问题。这些增量算法包括ISM、GSP+和MFS+。每种增量算法都有自己的特点,在不同的场景下分别进行了研究和评估。本文对增量算法及其非增量算法的相对性能进行了全面研究。我们的目标是在给定序列数据库的各种特征的情况下,为解决增量更新问题的算法选择提供指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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