The concept of patterns is the basis of sequence analysis. There are various pattern
definitions for biological data, texts, and time series. Inspired by the methodology of three …

Nonoverlapping sequential pattern mining (SPM) is a data analysis task, which aims at
identifying repetitive sequential patterns with gap constraint in a set of discrete sequences …

Energy-efficiency related research has reached a growing interest in recent years due to the
imminent scarcity of non-renewable resources in our environment and the impending …

Gap constraint sequential pattern mining (SPM), as a kind of repetitive SPM, can avoid
mining too many useless patterns. However, this method is difficult for users to set a suitable …

Sequence pattern mining aims to discover frequent subsequences as patterns in a single
sequence or a sequence database. By combining gap constraints (or flexible wildcards) …

Approximate pattern matching not only is more general than exact pattern matching, but also
allows some data noise. Most of them adopt the Hamming distance to measure similarity …

Mining frequent patterns with periodic wildcard gaps is a critical data mining problem to deal
with complex real-world problems. This problem can be described as follows: given a …

Energy demand in typical home environments accounts for a significant fraction of the
overall consumption in industrialized countries. In such context, the heterogeneity of the …

Patterns/subsequences frequently appearing in sequences provide essential knowledge for
domain experts, such as molecular biologists, to discover rules or patterns hidden behind …

Pattern matching (PM) with gap constraints (or flexible wildcards) is one of the essential
tasks in repetitive sequential pattern mining (or sequence pattern mining), since it can …