Abstract: Constraining sequential data expressing sequential data which a sequential pattern to be extracted must include is specified in advance. Sequential pattern candidates with sequence length 1 are initially determined from among a plurality of input sequential data. Next, a set of sequential pattern candidates is generated by determining a plurality of new sequential pattern candidates by elongating the sequence length of the sequential pattern candidates. In this sequential pattern candidate set, after sequential pattern candidates which can generate only a sequential pattern which does not include constraining sequential data are eliminated, sequential data which include constraining data, and frequently appear are extracted as a new sequential pattern.

Abstract: Constraining sequential data expressing sequential data which a sequential pattern to be extracted must include is specified in advance. Sequential pattern candidates with sequence length 1 are initially determined from among a plurality of input sequential data. Next, a set of sequential pattern candidates is generated by determining a plurality of new sequential pattern candidates by elongating the sequence length of the sequential pattern candidates. In this sequential pattern candidate set, after sequential pattern candidates which can generate only a sequential pattern which does not include constraining sequential data are eliminated, sequential data which include constraining data, and frequently appear are extracted as a new sequential pattern.

Abstract: A time-series data analyzing apparatus which extracts a composite factor time-series pattern from time-series data. The apparatus includes a dividing device which divides the time-series data into pattern generation time-series data and pattern inspection time-series data which do not include pattern generation time-series data. A first generating device generates a transitional pattern including a support time data indicating a transition of support time and having a transition occurrence probability higher than a minimum occurrence probability in the pattern generation time-series data. A second generating device generates frequently appearing integrated transitional patterns. A second computing device computes cause-and-effect strength of each of the frequently appearing integrated transitional patterns using the pattern inspection time-series data.

Abstract: A time-series data analyzing apparatus which extracts a composite factor time-series pattern from time-series data. The apparatus includes a dividing device which divides the time-series data into pattern generation time-series data and pattern inspection time-series data which do not include pattern generation time-series data. A first generating device generates a transitional pattern including a support time data indicating a transition of support time and having a transition occurrence probability higher than a minimum occurrence probability in the pattern generation time-series data. A second generating device generates frequently appearing integrated transitional patterns. A second computing device computes cause-and-effect strength of each of the frequently appearing integrated transitional patterns using the pattern inspection time-series data.

Abstract: Constraining sequential data expressing sequential data which a sequential pattern to be extracted must include is specified in advance. Sequential pattern candidates with sequence length 1 are initially determined from among a plurality of input sequential data. Next, a set of sequential pattern candidates is generated by determining a plurality of new sequential pattern candidates by elongating the sequence length of the sequential pattern candidates. In this sequential pattern candidate set, after sequential pattern candidates which can generate only a sequential pattern which does not include constraining sequential data are eliminated, sequential data which include constraining data, and frequently appear are extracted as a new sequential pattern.