A provenance method, system, and non-transitory computer readable medium for a plurality of eidetic systems having logs, include a log-segment clustering circuit configured to crawl the logs of each of the eidetic systems to cluster segments across the logs of temporally correlated events into clustered segments, a probabilistic interleaving circuit configured to analyze the correlated segments to interleave an order of processes in the logs and assign a probability to the order of the processes occurring, and a probabilistic linearization circuit configured to create a probability tree which includes a total probability that a process in the clustered segments causes a next process in the clustered segments until an end of the temporal event of the clustered segments for each of the interleaved order of processes interleaved by the probabilistic interleaving circuit.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A provenance system for a plurality of eidetic systems having logs, the system comprising: a log-segment clustering circuit configured to crawl the logs of each of the eidetic systems to cluster segments across the logs of temporally correlated events into clustered segments; a probabilistic interleaving circuit configured to analyze the correlated segments to interleave an order of processes in the logs and assign a probability to the order of the processes occurring; and a probabilistic linearization circuit configured to create a probability tree which includes a total probability that a process in the clustered segments causes a next process in the clustered segments until an end of the temporal event of the clustered segments for each of the interleaved order of processes interleaved by the probabilistic interleaving circuit. 2. The system of claim 1, wherein the correlated events are causally linked. 3. The system of claim 1, wherein the probabilistic interleaving circuit interleaves the order of processes in the logs using a clock-drift analysis between the provenance system and each of the plurality of eidetic systems. 4. The system of claim 1, wherein the logs of each of the plurality of eidetic systems are not exchanged to another eidetic system of the plurality of eidetic systems when the log-segment clustering circuit crawls the logs of each of the eidetic systems. 5. The system of claim 1, wherein the probability tree comprises a probabilistic linearization of the interleaved processes of the logs. 6. The system of claim 1, wherein an end user analyzes the logs using probabilistic lineage queries on the probability tree. 7. The system of claim 1, wherein an end user analyzes the logs using a rollback of the temporally correlated events via the probability tree. 8. The system of claim 1, wherein an end user analyzes the logs using a replay of the temporally correlated events via the probability tree. 9. The system of claim 1, wherein the probabilistic linearization circuit creates the probability tree such that all data structures of the logs are exposed to an end user. 10. The system of claim 1, wherein the probability tree comprises all data structures of the logs for the temporally correlated events such that all of the data structures of the logs are exposed to an end user. 11. A provenance method for a plurality of eidetic systems having logs, the method comprising: clustering segments across the logs of temporally correlated events into clustered segments by crawling the logs of each of the eidetic systems; interleaving an order of processes in the logs to assign a probability of the order of the processes occurring; and creating a probability tree which includes a total probability that a process in the clustered segments causes a next process in the clustered segments until an end of the temporal event of the clustered segments for each of the interleaved order of processes by the interleaving. 12. The method of claim 11, wherein the correlated events are causally linked. 13. The method of claim 11, wherein the interleaving interleaves the order of process in the logs using a clock-drift analysis between each of the plurality of eidetic systems. 14. The method of claim 11, wherein the creating creates the probability tree such that all data structures of the logs are exposed to an end user. 15. The method of claim 11, wherein the probability tree comprises all data structures of the logs for the temporally correlated events such that all of the data structures of the logs are exposed to an end user. 16. A non-transitory computer-readable recording medium recording a provenance program for a plurality of eidetic systems having logs, the program causing a computer to perform: clustering segments across the logs of temporally correlated events into clustered segments by crawling the logs of each of the eidetic systems; interleaving an order of processes in the logs to assign a probability of the order of the processes occurring; and creating a probability tree which includes a total probability that a process in the clustered segments causes a next process in the clustered segments until an end of the temporal event of the clustered segments for each of the interleaved order of processes by the interleaving. 17. The non-transitory computer-readable recording medium of claim 16, wherein the correlated events are causally linked. 18. The non-transitory computer-readable recording medium of claim 16, wherein the interleaving interleaves the order of process in the logs using a clock-drift analysis between each of the plurality of eidetic systems. 19. The non-transitory computer-readable recording medium of claim 16, wherein the creating creates the probability tree such that all data structures of the logs are exposed to an end user. 20. The non-transitory computer-readable recording medium of claim 16, wherein the probability tree comprises all data structures of the logs for the temporally correlated events such that all of the data structures of the logs are exposed to an end user.