A method is known for identifying a cause and effect relationship between events of equipment by using a Bayesian network, but it has been difficult to comprehensively gather events relating to people. Additionally, there is no known method for estimating the time at which other events occur between two or more events. Provided is an information processing apparatus including a target information obtaining section that obtains known event information relating to at least one known event that has occurred for a target; an information processing apparatus that obtains statistical data relating to events; and an event information generating section that generates unknown event information relating to an unknown event of the target, based on the statistical data and the known event information.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An information processing apparatus comprising: a target information obtaining section that obtains known event information relating to at least one known event that has occurred for a target; an information processing apparatus that obtains statistical data relating to events; and an event information generating section that generates unknown event information relating to an unknown event of the target, based on the statistical data and the known event information. 2. The information processing apparatus according to claim 1, comprising: a probability calculating section that calculates an event occurrence probability based on the statistical data. 3. The information processing apparatus according to claim 2, wherein the probability calculating section calculates an occurrence probability of a second event occurring if a first event occurs. 4. The information processing apparatus according to claim 2, wherein the probability calculating section calculates an occurrence probability of a second event occurring if a first event occurs, for each time interval of the first event and the second event. 5. The information processing apparatus according to claim 1, further comprising: a BN generating section that generates a Bayesian network (BN) including a plurality of events as nodes, based on the event occurrence probability, wherein the event information generating section generates the unknown event information based on the Bayesian network. 6. The information processing apparatus according to claim 5, wherein the BN generating section generates a conditional probability table having time intervals, for each node in the Bayesian network. 7. The information processing apparatus according to claim 6, wherein the event information generating section estimates a time at which the unknown event of the target occurred, based on the conditional probability table having time intervals. 8. The information processing apparatus according to claim 7, wherein the occurrence time estimating section estimates the time interval of the unknown event of the target to be a time interval during which the occurrence probability is highest in the conditional probability table having time intervals. 9. The information processing apparatus according to claim 7, wherein the occurrence time estimating section identifies a time interval of three or more events, based on a sum or product of the occurrence probabilities of two or more time intervals included between the three or more events in the conditional probability table having time intervals, and the information processing apparatus estimates the time at which the unknown event of the target occurred based on the identified time interval. 10. The information processing apparatus according to claim 9, wherein the occurrence time estimating section identifies the time interval of the three or more events to be a time interval in which the sum or product of the occurrence probabilities of the two or more time intervals included between the three or more events in the conditional probability table having time intervals is highest, where the sum of the two or more time intervals does not exceed a time interval of a first event and a time interval of a last event among the three or more events, and the information processing apparatus estimates the time at which the unknown event of the target occurred based on the identified time interval. 11. The information processing apparatus according to claim 5, wherein the event information generating section includes an occurrence estimating section that estimates whether the unknown event of the target has occurred for the target from the known event information, based on the Bayesian network. 12. The information processing apparatus according to claim 11, further comprising: a recommend generating section that generates information to be recommended to the target in relation to the unknown event, based on the unknown event information. 13. The information processing apparatus according to claim 12, wherein the event information generating section generates unknown event information indicating that an unknown event whose occurrence probability of having occurred for the target is greater than or equal to a threshold value has occurred for the target, and the recommend generating section generates the information to be recommended for the unknown event whose unknown event information indicates that the unknown event has occurred for the target. 14. The information processing apparatus according to claim 1, wherein the information processing apparatus: obtains first-order statistical information from an external server; generates statistical data by gathering the first-order statistical information; obtains synonym data including a plurality of expressions relating to events; and obtains statistical data relating to two events, by matching an expression of the statistical data that matches expressions relating to the two events, based on the synonym data. 15. The information processing apparatus according to claim 5, wherein the information processing apparatus obtains the statistical data for each category of the events; the BN generating section identifies a category with which the target is associated, based on an association of the target; and the event information generating section generates the unknown event information based on the statistical data of the category with which the target is associated. 16. The information processing apparatus according to claim 1, wherein the event is a life event relating to the target. 17. An information processing method performed by a computer, comprising: obtaining known event information relating to at least one known event that has occurred for a target; obtaining statistical data relating to events; and generating unknown event information relating to an unknown event of the target, based on the statistical data and the known event information. 18. The information processing method according to claim 17, comprising: calculating an event occurrence probability based on the statistical data. 19. The information processing method according to claim 18, wherein the calculating includes calculating an occurrence probability of a second event occurring if a first event occurs. 20. The information processing method according to claim 18, wherein the calculating includes calculating an occurrence probability of a second event occurring if a first event occurs, for each time interval of the first event and the second event. 21. A program that, when executed by a computer, causes the computer to function as: a target information obtaining section that obtains known event information relating to at least one known event that has occurred for a target; an information processing apparatus that obtains statistical data relating to events; and an event information generating section that generates unknown event information relating to an unknown event of the target, based on the statistical data and the known event information. 22. The program according to claim 21, further causing the computer to function as: a probability calculating section that calculates an event occurrence probability based on the statistical data. 23. The program according to claim 22, wherein the probability calculating section calculates an occurrence probability of a second event occurring if a first event occurs. 24. The program according to claim 22, wherein the probability calculating section calculates an occurrence probability of a second event occurring if a first event occurs, for each time interval of the first event and the second event. 25. A storage medium storing thereon the program according to claim 21.