This invention provides a monitoring device and the like which exhibit high capability of detecting a state related to a system even when the system allows a plurality of objects to be monitored to complexly cooperate with each other. A monitoring device 1 includes a first model generation unit which divides, of first time-series information related to an object to be monitored, second time-series information associated with each item and generates models related to the pieces of divided information, and a determination unit which by applies third time-series information to the models to determine whether a correlation is maintained and performs determination related to each item based on results of the determining.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A monitoring device comprising: model generation unit, implemented by a processor, for dividing time-series information from among pieces of time-series information obtained by associating pieces of information of a plurality of items related to an object to be monitored on a time-series basis over a predetermined period, the time-series information associated with each item to be modeled, into pieces of divided information of periods, each period shorter than the predetermined period, and generating models representing correlations related to the pieces of divided information; and determination unit, implemented by a processor, for, by applying another time-series information obtained by associating the pieces of information of the plurality of items on a time-series basis during a period different from the predetermined period, to at least two or more of the models related to the each item, for each of the two or more of the models, determining whether the correlation represented by at least one or more of the models is maintained, and performing a determination related to the each item based on results of the determining. 2. The monitoring device according to claim 1, wherein the model generation unit divides the time-series information associated with the each item, in response to a change in state related to the each item. 3. The monitoring device according to claim 1, wherein the model generation unit divides the time-series information associated with the each item, in response to a change in state related to the object to be monitored. 4. The monitoring device according to claim 1, wherein the model generation unit divides the time-series information associated with the each item, on the basis of a predetermined number. 5. The monitoring device according to claim 1, wherein the determination unit performs determination related to the each item, on the basis of at least one of the results. 6. The monitoring device according to claim 5, wherein the determination unit determines an anomaly for the each item by determining whether a smallest one of first prediction errors for the time-series information of the plurality of items during the different period satisfies a range defined by a predetermined error threshold, for a correlation function represented by the at least one or more of the models. 7. The monitoring device according to claim 5, wherein the determination unit determines an anomaly for the each item by determining whether all of first prediction errors for the time-series information of the plurality of items during the different period satisfy a range defined by a predetermined error threshold, for a correlation function represented by the at least one or more of the models. 8. The monitoring device according to claim 5, wherein as the determination related to the each item, the determination unit selects a smallest one of first prediction errors for the time-series information of the plurality of items during the different period, for a correlation function represented by the at least one or more of the models. 9. The monitoring device according to claim 1, wherein the model generation unit divides the time-series information associated with the each item, on the basis of a plurality of division conditions, generates the at least one or more of the models related to the pieces of divided time-series information, obtains a total amount of change between the at least one or more generated model, and divides the time-series information associated with the each item, in accordance with a division condition under which the total amount of change is largest of the obtained total amount of change. 10. The monitoring device according to claim 1, further comprising: selection unit, implemented by the processor, for selecting time-series information associated with the specific each item, for which weight information representing a weight for the model generated by the model generation unit satisfies a first condition, of the time-series information associated with the each item, and at least one or more of the models related to the each item, wherein the determination unit applies the time-series information of the plurality of items during the different period to the at least two or more of the models related to the specific each item selected by the selection unit to determine whether the correlations represented by the at least one or more selected model is maintained, and performs determination related to the each item based on results of the former determination. 11. The monitoring device according to claim 1, further comprising: model determination unit, implemented by the processor, for determining whether the at least one or more of the models matches a state related to the each item, and, upon determining that the at least one or more of the models does not match the state, providing information representing a division condition for the time-series information associated with the each item to the models generation unit and issuing a request to regenerate the model related to time-series information generated in accordance with the division condition, wherein the model generation unit generates newly divided time-series information on the basis of at least one or more the pieces of the divided time-series information used to generate the models determined not to match, in accordance with the division condition obtained from the model determination unit. 12. The monitoring device according to claim 11, wherein the model determination unit determines whether a difference between parameters included in the at least one or more of the models, which is obtained on the basis of the parameters, satisfies a second condition, and, upon determining that the difference does not satisfy the second condition, determines that the model for which the difference is obtained does not match the state related to the each item, and provides information representing the division condition for issuing an instruction to combine the at least one or more the pieces of divided time-series information used to generate the models determined not to match. 13. The monitoring device according to claim 11, wherein when the model comprises at least two or more of the models, the model determination unit determines that the at least one or more of the models does not match the state related to the each item, and provides information representing the division condition for issuing an instruction to combine the at least one or more the pieces of divided time-series information used to generate all of the models for which the weight information related to the models satisfies a third condition. 14. The monitoring device according to claim 1, wherein the determination unit presents the time-series information and a division boundary in the time-series information divided by the model generation unit, in a mode identifiable for a user. 15. The monitoring device according to claim 1, wherein the determination unit presents in a mode identifiable for a user, the time-series information of the plurality of items during the period different from the predetermined period, and at least one or more of the results of the determination used for the determination related to the each item. 16. A monitoring system comprising: the monitoring device according to claim 1; and at least one or more object to be monitored communicably connected to the monitoring device via a communication network, wherein the object to be monitored obtains pieces of information concerning the plurality of items for each predetermined time interval, and the monitoring device performs determination related to the object to be monitored based on the time-series information obtained by associating the pieces of information concerning the plurality of items related to the object to be monitored over a predetermined period. 17. A monitoring method comprising: dividing time-series information from among pieces of time-series information obtained by associating pieces of information of a plurality of items related to an object to be monitored on a time-series basis over a predetermined period, the time-series information associated with each item to be modeled, into pieces of divided information of periods, each period shorter than the predetermined period, and generating models representing correlations related to the pieces of divided information; and by applying another time-series information obtained by associating the pieces of information of the plurality of items on a time-series basis during a period different from the predetermined period, to at least two or more of the models related to the each item, for each of the two or more of the models, determining whether the correlation represented by at least one or more of the models is maintained, and performing a determination related to the each item based on results of the determining. 18. A recording medium in which a computer program is stored, the program causing a computer to implement the functions of: dividing time-series information from among pieces of time-series information obtained by associating pieces of information of a plurality of items related to an object to be monitored on a time-series basis over a predetermined period, the time-series information associated with each item to be modeled, into pieces of divided information of periods, each period shorter than the predetermined period, and generating models representing correlations related to the pieces of divided information; and by applying another time-series information obtained by associating the pieces of information of the plurality of items on a time-series basis during a period different from the predetermined period, to at least two or more of the models related to the each item, for each of the two or more of the models, determining whether the correlation represented by at least one or more of the models is maintained, and performing a determination related to the each item based on results of the determining.