A time-series data processing device comprising: an event waveform extracting unit adapted to extract waveform data, estimated to change because of an event having occurred in a subject equipment, from each of a plurality of first time-series data sequentially observed over time from the subject equipment, wherein the event waveform extracting unit is adapted to extract the waveform data on a basis of a combination of partial string data whose values continuously increase or decrease in the first time-series data; a co-occurrence rate calculating unit adapted to calculate a co-occurrence rate of the waveform data extracted by the event waveform extracting unit among the first time-series data; a grouping unit adapted to classify the first the time-series data into groups depending on the co-occurrence rate of the waveform data calculated by the co-occurrence rate calculating unit ; an event information generating unit adapted to determine time at which periods of occurrence of the waveform data overlap with each other among the first time-series data included in a group into which the first time-series data are classified by the grouping unit , and to generate event information identifying an event related to the waveform data on a basis of the determined time; a time-series data acquiring unit adapted to acquire second time-series data observed by a sensor provided in the subject equipment when determining abnormality of the subject equipment; a detecting unit adapted to detect outlier data from the second time-series data, the outlier data being partial string data falling within an abnormality range; and a determining unit adapted to determine abnormality of the subject equipment on a basis of the outlier data detected by the detecting unit and the event information generated by the event information generating unit . an event waveform extracting unit adapted to extract waveform data, estimated to change because of an event having occurred in a subject equipment, from each of a plurality of first time-series data sequentially observed over time from the subject equipment, wherein the event waveform extracting unit is adapted to extract the waveform data on a basis of a combination of partial string data whose values continuously increase or decrease in the first time-series data; a co-occurrence rate calculating unit adapted to calculate a co-occurrence rate of the waveform data extracted by the event waveform extracting unit among the first time-series data; a grouping unit adapted to classify the first the time-series data into groups depending on the co-occurrence rate of the waveform data calculated by the co-occurrence rate calculating unit ; an event information generating unit adapted to determine time at which periods of occurrence of the waveform data overlap with each other among the first time-series data included in a group into which the first time-series data are classified by the grouping unit , and to generate event information identifying an event related to the waveform data on a basis of the determined time; a time-series data acquiring unit adapted to acquire second time-series data observed by a sensor provided in the subject equipment when determining abnormality of the subject equipment; a detecting unit adapted to detect outlier data from the second time-series data, the outlier data being partial string data falling within an abnormality range; and a determining unit adapted to determine abnormality of the subject equipment on a basis of the outlier data detected by the detecting unit and the event information generated by the event information generating unit . <EOS>