一般间隙及一次性条件的严格模式匹配

具有间隙约束的模式匹配是序列模式挖掘的关键问题之一.一次性条件约束是要求序列中每个位置的字符最多只能使用一次,在序列模式挖掘中采用一次性条件约束更加合理.但是目前,间隙约束多为非负间隙,非负间隙对字符串中每个字符的出现顺序具有严格的约束,一定程度上限定了匹配的灵活性.为此,提出了一般间隙及一次性条件的严格模式匹配问题;之后,理论证明了该问题的计算复杂性为NP-Hard问题.为了对该问题进行有效求解,在网树结构上构建了动态更新结点信息的启发式求解算法(dynamically changing node property,简称DCNP).该算法动态地更新各个结点的树根路径数、叶子路径数和树根-叶子路径数等,进而每次可以获得一个较优的出现;之后,迭代这一过程.为了有效地提高DCNP算法速度,避免动态更新大量的结点信息,提出了Checking机制,使得DCNP算法仅在可能产生内部重复出现的时候才进行动态更新.理论分析了DCNP算法的时间复杂度和空间复杂度.大量实验结果验证了DCNP算法具有良好的求解性能.

Strict Pattern Matching with General Gaps and One-Off Condition

Pattern matching with gap constraints is one of the key issues of sequential pattern mining. One-off condition which is always used in sequential pattern mining tasks means that the character of each position in the sequence can be used at most once for pattern matching. Recently, most researches focus on pattern matching with non-negative gaps, but the rule of non-negative gaps implies the character's order in the sequence may limit the flexibility of matching. For these reasons, this article proposes a strict pattern matching with general gaps and one-off condition and shows that this problem is NP-hard. To tackle this issue, a heuristic algorithm, named dynamically changing node property (DCNP), is designed based on nettree which dynamically updates the properties of each node such as the numbers of root paths, leaf paths and root-leaf paths, and thus can get a better occurrence. The above process is then iterated. To effectively improve the speed of DCNP and avoid dynamically updating information of nodes on a large scale, a checking mechanism is applied to allow DCNP update information of nodes only when the occurrence may have repetition. The space and time complexities of DCNP are also analyzed. Experimental results show that DCNP has better performance than other competitive algorithms.