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引用次数: 3
摘要
在本文中,我们提出了一个Erlang的高效索引结构的实现,称为序列二进制决策图(seqbdd),用于在大型序列数据中发现知识。最近,Loekito, Bailey, and Pei (KAIS, 2009)提出了SeqBDD。seqbdd是一种紧凑的索引,用于有效地表示序列集。此外,seqbdd为序列集提供了丰富的操作集合,这对于实现序列挖掘算法非常有用。我们提出SeqBDD作为强大的字符串处理框架,Erlang是适合SeqBDD的语言。SeqBDD系统大量使用哈希表来避免冗余的内存和计算。我们用ETS实现了SeqBDD包的哈希表。
In this paper, we present an implementation of Erlang of an efficient index structure, called Sequence Binary Decision Diagrams (SeqBDDs), for knowledge discovery in large sequence data. Recently, Loekito, Bailey, and Pei (KAIS, 2009) proposed SeqBDD. SeqBDDs are a compact indices for efficiently representing the set of sequences. Furthermore, SeqBDDs provide a rich collection of operations for sets of sequences, which are useful for implementing sequence mining algorithms. We propose SeqBDDs as powerful framework for string processing and Erlang is appropriate language for SeqBDD. SeqBDD system heavily uses hash tables to avoid redundant memory and computation. We implemented SeqBDD package with ETS for hash tables.