Storing the repository origin of data inputs within a knowledge store

• US 7,716,241 B1
• Filed: 10/27/2004
• Issued: 05/11/2010
• Est. Priority Date: 10/27/2004
• Status: Active Grant

• Current Assignee: Unisys Corporation
• Original Assignee: Unisys Corporation
• Inventors: Claar, Jane Van Keuren, Mazzagatti, Jane Campbell
• Primary Examiner(s): Fleurantin; Jean B
• Application Number:
  US10/975,332
• Time in Patent Office: 2,022 Days
• Field of Search: 707 1- 10, 707100-1041, 707200-206
• US Class Current: 707/782
• CPC Class Codes: G06F 16/2246 Trees, e.g. B+trees

Abstract

An effective means for building an interlocking trees datastore from multiple data sources that contained within the datastore the knowledge of the origin of the data was needed, and is thus described herein. Should it be desired or necessary to identify the different sources of data within the Kstore data structure, the present invention teaches how an additional field for the origin of the data is created, how the origin of the data is stored in that newly created field, and how the interlocking trees data store takes that field and creates nodes within the structure, therefore embedding the origin information within the knowledge contained in the Kstore data structure.

Claims

1. A method of storing data from a plurality of data sources into an interlocking trees datastore within memory of a computing system comprising a KStore, whereby said sources of data remain distinguishable for each data stream from said plurality of data sources when stored into said interlocking trees datastore, said method comprising:

receiving a sequence from a stream of data from a first one of said plurality of data sources,

identifying by associating with said sequence, an identity indicator that indicates from which one of said plurality of sources said sequence originated,

creating a particle stream based on said sequence and said identity indicator and sending said particle stream to said interlocking trees data store within the memory of the computing system via a K Engine, said interlocking trees data store comprising nodes and non-root nodes organized into a plurality of connected trees, the plurality of connected trees comprising an asCase tree and at least one of a plurality of asResult trees, the asCase tree comprising a first root and at least one of a plurality of non-root nodes, the at least one non-root node comprising a first Case node, and the at least one asResult tree comprising a second root node representing a particle of the particle stream and at least one of a plurality of non-root nodes common with the nodes of the asCase tree, the at least one non-root node common with the nodes of the asCase tree comprising a first Result node, the interlocking trees data store comprising asCase and asResult paths, wherein an asCase path comprises a sequence of sub-component nodes linked with bi-directional asCase links ending with an end-product node and where each sub-component node in the asCase path has a bi-directional asResult link to an elemental root node or end-product node, comprising an asResult path.

2. The method of claim 1 in which said step of identifying by associating an identity indicator with said sequence occurs in an application level component, and wherein a said application level component connects to said first one of said plurality of data sources, comprising:

data is sent from said first data source to said application level component,

establishing an identity indicator based on said sent data.

3. The method of claim 2 further comprising after sending data from said first data source to said application level component, identifying in said sent data, said first data source.

4. The method of claim 2 wherein said application level component creates a stream for said Learn Engine from said first data source and in so doing incorporates said identity indicator into data for each sequence from said first data source.

5. The method of claim 4 wherein said application level component is an Extract, Translate and Load or a Filter function component.

6. The method of claim 2 wherein said application level component receives data from said first one of said plurality of data sources in data source sending format and configures it to be in a format that has only the data desired.

7. The method of claim 6 wherein the data desired is determined by an applications developer.

8. The method of claim 6 wherein the data desired is predetermined.

9. The method of claim 2 wherein said application level component removes HTML Tags and delimiters from data from said first one of said plurality of data sources.

10. The method of claim 2 wherein said application level component adds additional coincident reference data to said sequence.

11. The method of claim 10 wherein the additional coincident reference data is a time stamp.

12. The method of claim 10 wherein the additional coincident reference data is supplied by sensor reading from a monitoring device.

13. The method of claim 1 wherein for each data source said step of identifying by associating an identity indicator with said sequence occurs in an application level component, and wherein a said application level component connects to each one of said plurality of data sources, and said method comprises for each data source:

sending data from said each data source to said application level component,

establishing an identity indicator for said each source based on said sent data for data from said each source.

14. The method of claim 13 further comprising after sending data from said first data source to said application level component, identifying in said sent data, said first data source.

15. The method of claim 13 wherein said application level component creates a stream for said Learn Engine from said each data source and in so doing incorporates said identity indicator into data for each sequence from said each data source identifying data for each sequence from the particular one of said each data sources from which said each sequence originates.

16. The method of claim 1 wherein said process of identifying by associating an identity indicator with said sequence occurs in a Learn Engine, and wherein said Learn Engine is configured by a application developer directed or by an application directed configuration process in which at least some of said plurality of data sources is provided with an identity indicator prior to said Learn Engine receiving substantially any data from said at least some of said plurality of data sources.

17. The method of claim 16 wherein said process of identifying said identity indicator with said sequence is accomplished by a Learn Engine, said Learn Engine organizing said sequence so as to send a particle stream to said K Engine, whereby said identity indicator is included within said particle stream.

18. The method of claim 1 further comprising recording in an interlocking trees datastore an event for said identity indicator.

19. The method of claim 18 wherein said recording in an interlocking trees datastore of said event for said identity indicator comprises:

creating a node in said interlocking trees datastore for said identity indicator, and

integrating said identity indicator node into a path within said interlocking trees datastore for said sequence.

20. The method of claim 18 wherein said sequence is recorded in an interlocking trees datastore as a series of events including said identity indicator whereby for each particle of said sequence a count is added to all nodes and a pointer to a node at the end of the sequence is returned by said K Engine.

21. A computer readable storage medium including digitally encoded data readable by a processing system providing a KStore stored therein, the KStore comprising an interlocking trees datastore structure comprising nodes and non-root nodes organized into a plurality of connected trees, the plurality of connected trees comprising an asCase tree and at least one of a plurality of asResult trees, the asCase tree comprising a first root and at least one of a plurality of non-root nodes, the at least one non-root node comprising a first Case node, and the at least one asResult tree comprising a second root node representing a particle of a particle stream and at least one of a plurality of non-root nodes common with the nodes of the asCase tree, the at least one non-root node common with the nodes of the asCase tree comprising a first Result node, the interlocking trees data store comprising asCase and asResult paths, wherein an asCase path comprises a sequence of sub-component nodes linked with bi-directional asCase links ending with an end-product node, wherein each sub-component node in the asCase path has a bi-directional asResult link to an elemental root node or end-product node comprising an asResult path, said KStore having at least a plurality of repository ID nodes identifying a given repository as a data source for each sequence of particles in the particle stream from said given repository that is recorded by said KStore within memory of a computing system.

22. The computer readable storage medium of claim 21 wherein said plurality of repository ID nodes are recorded in memory in a location logically just after a BOT node for said sequence from said given repository so that it is recorded as a first node of said sequence.

23. The computer readable storage medium of claim 21 wherein at least one of said plurality of repository ID nodes is different from at least one other of said plurality of repository ID nodes.