Functional operations for accessing and/or building interlocking trees datastores to enable their use with applications software

• US 7,593,923 B1
• Filed: 06/29/2004
• Issued: 09/22/2009
• Est. Priority Date: 06/29/2004
• Status: Active Grant

• Current Assignee: Unisys Corporation
• Original Assignee: Unisys Corporation
• Inventors: Phan, Tony T., Claar, Jane Van Keuren, Mazzagatti, Jane Campbell
• Primary Examiner(s): Alam; Hosain T
• Assistant Examiner(s): JOHNSON, JOHNESE T
• Application Number:
  US10/879,329
• Time in Patent Office: 1,911 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2246 Trees, e.g. B+trees
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching

Abstract

A set of mechanisms handles communication with a Knowledge Store and its K Engine(s). The Knowledge Store (Kstore) does not need indexes or tables to support it but instead is formed by the construction of interlocking trees of pointers in nodes of the interlocking trees. The K Engine builds and is used to query a KStore by using threads that use software objects together with a K Engine to learn particlized events, thus building the KStore, and these or other software objects can be used to make queries and get answers from the KStore, usually with the help of a K Engine. Under some circumstances, information can be obtained directly from the KStore, but is generally only available through the actions of the K Engine. The mechanisms provide communications pathways for users and applications software to build and/or query the KStore. Both these processes can proceed simultaneously, and in multiple instances. There can be a plurality of engines operating on a KStore essentially simultaneously. Additionally a mechanism for providing triggers allows for automatic reporting of events, conditions and occurrences to users and applications.

Claims

1. A system component for accessing an interlocking trees datastore in an interlocking trees datastore system, said system component comprising:

a segment executing at least in part on a computer, said segment receiving calls from other system components, said other system components including at least one of a Learn Engine, said Learn Engine receiving data from at least one of a plurality of sources and transforming said data into particles, said particles added to said interlocking trees datastore by said segment or an API Utility, said API Utility processing inquiries for information from said interlocking trees datastore and processing requests to add information to said interlocking trees datastore, said segment finding a location within said interlocking trees datastore for a particle of said particles associated with at least a one of said calls, said interlocking trees datastore comprising a first tree depending from a first root node and including at least one of a plurality of branches, wherein each of the plurality of branches ends in an end product node comprising a leaf node, said interlocking trees datastore further comprising a second root of a second tree linked to each end product node, said interlocking trees datastore further comprising at least a third tree, wherein a root of the third tree comprises an elemental node representing a particle, the root of the third tree linked to at least one node in at least one branch of the first tree;

wherein the interlocking trees datastore comprises;

an interlocking trees datastore comprising a plurality of K nodes;

each K node of the plurality of nodes comprises a Case pointer and a Result pointer;

said Case pointer and said Result pointer pointing to two nodes from which said K node is formed;

said K node also comprising pointers to an asCase array and an asResult array;

said asCase array comprising pointers to nodes whose Case pointers point to said K node; and

said asResult array comprises pointers to nodes whose Result pointers point to said K node.

2. The system component of claim 1 wherein said system component is called a K Engine and said interlocking trees datastore is a KStore.

3. The system component of claim 1 wherein said system component builds said interlocking trees datastore only on condition a learn switch is in a learn state, said build accomplished by said system component recording said particle as an event in said interlocking trees datastore.

4. The system component of claim 1 wherein said system component receives from said other system components in said call, pointers associated with said particle, said pointers indicative of a current location in an interlocking trees datastore of said interlocking trees datastore system.

5. The system component of claim 1 wherein said system component has means to maintain a sensor list to compare sensors from said list to said particles, each of said sensors on said list associated to an elemental root node in said interlocking trees datastore.

6. The system of claim 5 wherein said pointers associated with said particle identify at least a last location within said interlocking trees datastore, and wherein said system component has link determining means which in response to determining that said last location is linked to a one of said elemental root nodes through a next subcomponent node, said link determining means establishes an existing location of said next subcomponent node linked to said elemental root node of said particle as a new current location in the interlocking trees datastore.

7. The system of claim 6 wherein said linked to one of said elemental root nodes is associated to a sensor on said sensor list which matches said particle.

8. The system of claim 6 wherein said link determining means also determines that said link from said last location to said elemental root node of said particle is indirect, wherein said indirectness is a determination that said particle is linked through a subcomponent node other than said next subcomponent node in said interlocking trees datastore.

9. The system of claim 6 wherein in response to said link determining means determining that said last location is linked to an elemental root node through a subcomponent node, the location of the next subcomponent node is established as the new current location and a counter in said elemental root node of said particle is caused by said link determining means to be incremented.

10. The system of claim 6 wherein said pointers associated with said particle identify at least a last location within said interlocking trees datastore, and wherein in response to determining said last location is determined by said link determining means not to be linked to an elemental root node through the next subcomponent node of said particle, then said system component causes the formation of a new subcomponent node for said particle in said interlocking trees datastore.

11. The system of claim 8 wherein in response to said link determining means determining that a particle is a termination of thought comprising a completion of an input entity, said system component activates a formation of end product node routine to cause the formation of an end product node in said interlocking trees datastore;

wherein the particle corresponds to data stored within the interlocking datastore used within the KStore;

the thought corresponds to data interconnected within the interlocking datastore as a sequence of K nodes that represent a sequence of events;

the termination of thought corresponds to a K node indicating an end of the sequence of k nodes corresponding to the end of a thought; and

the end of product node corresponds to the k node representing the termination of thought.

12. The system of claim 11 wherein said determination that a particle is a termination of thought depends upon finding a delimiter.

13. The system of claim 12 wherein in response to determining said delimiter is a delimiter for a higher level, adding end of thought nodes for each level between a current level and said higher level.

14. The system of claim 13 wherein in response to determining said delimiter is for said higher level is for a highest existing level, adding a subcomponent node above said highest level.

15. The system of claim 11 wherein a delimiter in a message communicating said particle to said system component will identify to said link determining means that said particle is a termination of thought.

16. The system of claim 12 wherein said sensor list contains at least one delimiter as a sensor.

17. The system of claim 11 wherein in response to determining said particle is found to be a termination of a thought, said system component adds information about said end product node as a monad to a monad list.

18. The system component of claim 4 wherein said system component provides feedback to other system components that send particles in messages, said feedback accomplished by returning location pointer data after a one of said particles is submitted to said system component, wherein said returned location pointer data identifies the location of the subcomponent node through which the system component will have established a link to said particle is in said interlocking trees datastore.

19. The system component of claim 15 wherein said particle is supplied by said API Utility system component, or from said Learn Engine system component.

20. The system component of claim 4 wherein said system component is coupled to a memory segment storing state variables identifiable as switches, said state variables being applicable to any actions of said system component, wherein said state variables determine how said system component reacts to calls from said other system components.

21. The system component of claim 4 wherein said system component comprises a memory segment storing state variables for actions of said system component, wherein settings of said state variables determine how said system component reacts to calls from said other system components.

22. The system component of claim 17 wherein said state variables stored in said memory segment comprises at least one switch from a list of switches comprising:

Learn (Y or N), Column numbers (Y or N), Meta Data field names used instead of column numbers (Y or N), EOT levels (Number and names;

EOTCOL (column name), EOTVAR (variable), EOTFLD (field entry), EOTRCD (record).

23. The system component of claim 17 wherein said additional information stored in said memory segment comprises at least one switch setting for enabling and disabling a trigger to store a notification signal from said system component to cause said system component to send said notification signal when a triggering event or condition has occurred.

24. The system component of claim 17 wherein said switches for enabling and disabling triggers stored in said memory segment comprises at least one trigger from the list of triggers comprising:

New variable, New record, Fill in missing variables and log, or Verify selected fields.

25. The system component of claim 17 wherein said system component memory sensor list is managed by a sensor list manager of said system component, and wherein said sensor list manager operates in a configuration set by a state to determine a configuration in which to operate, said state being configurable by at least one switch, wherein in response to said sensor list manager receiving a particle that is not in said sensor list, said state sets said configuration to manage said particle that is not in said sensor list.

26. The sensor list manager of claim 25 wherein said configurable sensor list manager states comprise;

a state in which on the occurrence of receiving a particle that is not on said sensor list, no action is taken.

27. The sensor list manager of claim 25 wherein said configurable sensor list manager states comprise:

a state in which an error is sent on the occurrence of receiving said particle that is not on said sensor list.

28. The sensor list manager of claim 25 wherein said configurable sensor list manager states comprise:

a state in which a new sensor is added to said sensor list on the occurrence of said particle that is not on said sensor list.

29. The sensor list manager of claim 25 wherein said configurable sensor list manager states comprise:

a state in which a log is maintained to record said receipt of any said particles not on said sensor list.

30. The sensor list manager set forth in claim 25 wherein each of the sensor list manager states is set by a separate switch.

31. A method of accessing an interlocking trees datastore in an interlocking trees datastore system, said method comprising:

generating a call to a K Engine, said call requesting addition of a particle to said interlocking trees datastore and retrieval of pointer data from said interlocking trees datastore, said interlocking trees datastore comprising a first tree depending from a first root node and including at least one of a plurality of branches, wherein each of the plurality of branches ends in an end product node comprising a leaf node, said interlocking trees datastore further comprising a second root of a second tree linked to each end product node, said interlocking trees datastore further comprising at least a third tree, wherein a root of the third tree comprises an elemental node representing a particle, the root of the third tree linked to at least one node in at least one branch of the first tree,

processing in said K Engine, a response including said retrieved pointer data into a return message, and

returning said return message;

wherein the interlocking trees datastore comprises;

an interlocking trees datastore comprising a plurality of K nodes;

each K node of the plurality of nodes comprises a Case pointer and a Result pointer;

said Case pointer and said Result pointer pointing to two nodes from which said K node is formed;

said K node also comprising pointers to an asCase array and an asResult array;

said asCase array comprising pointers to nodes whose Case pointers point to said K node; and

said asResult array comprises pointers to nodes whose Result pointers point to said K node.

32. The method of claim 31 further comprising the step;

generating a next call, said next call having a new particle and containing said retrieved pointer data.

33. The method of claim 31 wherein said method further comprises:

in response to determining that a learn switch is set to learn, also recording said particle as an event in said interlocking trees datastore.

34. The method of claim 33 wherein in response to determining that said interlocking trees datastore nodes have counters, and said switch is set to learn and said particle is equivalent to a previously recorded particle event, recording a new such particle by incrementing a counter in an elemental root node associated with said retrieved pointer data.

35. A method of accessing an interlocking trees datastore in an interlocking trees datastore system, said method comprising:

preparing a message to send a particle to a K Engine, said K Engine adding said particle to said interlocking trees datastore, wherein in said preparing, determining whether a next particle in a chain of thought being prepared to send as a call via said message to said K Engine is a branch particle event, and in response to determining that said next particle is a branch particle, sending current location data for a previous to a last subcomponent node in said message, said next particle recorded in said interlocking trees datastore comprising a first tree depending from a first root node and including at least one of a plurality of branches, wherein each of the plurality of branches ends in an end product node comprising a leaf node, said interlocking trees datastore further comprising a second root of a second tree linked to each end product node, said interlocking trees datastore further comprising at least a third tree, wherein a root of the third tree comprises an elemental node representing a particle, the root of the third tree linked to at least one node in at least one branch of the first tree;

wherein the interlocking trees datastore comprises;

an interlocking trees datastore comprising a plurality of K nodes;

each K node of the plurality of nodes comprises a Case pointer and a Result pointer;

said Case pointer and said Result pointer pointing to two nodes from which said K node is formed;

said K node also comprising pointers to an asCase array and an asResult array;

said asCase array comprising pointers to nodes whose Case pointers point to said K node; and

said asResult array comprises pointers to nodes whose Result pointers point to said K node.