Pyramid Information Quantification or PIQ or Pyramid Database or Pyramided Database or Pyramided or Selective Pressure Database Management System

• US 20080215614A1
• Filed: 09/07/2006
• Published: 09/04/2008
• Est. Priority Date: 09/08/2005
• Status: Abandoned Application

• Current Assignee: Michael J. Slattery
• Original Assignee: Michael J. Slattery
• Inventors: Slattery, Michael J.
• Application Number:
  US11/470,748
• Publication Number:
  US 20080215614A1
• Time in Patent Office: Days
• US Class Current: 707/103R
• CPC Class Codes: G06F 16/217 Database tuning G06F16/2282 takes precedence; database performance monitoring G06F11/3409
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 16/95 Retrieval from the web

Abstract

Embodiments of the present invention allow for methods to catalog, classify and stratify data, producing an optimized and finitely targeted database, database subset or data model, including networks of any scale, and their contents. This would include World Wide Web pages and their objects or resources. Four controls and constraints: Category Target Time and Exclusion, produce a data environment that applies selective pressure to delineate stronger data or targeted data from weaker or unwanted data. A wide variety of free standing application(s), search engine(s), social network(s), database schema(s) and control(s) can all be derived from the inherent flexibility of the information-processing capabilities defined by the patent described herein.

Claims

1. A computer-implemented method to produce, structure and organize (schema);

producing a (data model) and interrogate, (query), a database, comprised of;

a

Category Database and Rule-set (Rule

     1); and

/or

Target Database and Rule-set (Rule

     2); and

/or

Time Rule-set (Rule

     3); and

/or

Exclusion Rule-set (Rule

     4); and

/or any combination of Rules 1, 2, 3 or 4, designed to accomplish information processing and/or produce an information processing system;

hereafter referred to as a Pyramid database or Pyramided database.

2. The method of claim 1, comprising:

one or more of the four rule-sets, wherein selective pressure is exerted upon the specified database resulting in an optimized query result.

3. The method of claim 1, comprising:

the results of, or product of, any type of Search Engine returning results from a Pyramided database.

4. The method of claim 1, comprising:

a Search Engine controlled by any combination of Rule-sets 1, 2, 3 or 4.

5. The method of claim 1, comprised of:

a specified database, configured as any shape, size, number of layers, depths, arrays, dimensions, be they contiguous or non-contiguous and containing any data;

data type(s);

data element(s);

cell(s);

web-site(s)/page(s);

document(s);

file(s);

object(s);

resource(s);

or record(s) wherein the contents can be processed or information processed by, but not limited to;

any one, any combination of, or all of the following;

text/word/set(s) mapping, text/word/set(s) matching, pattern matching, statistical scoring, ranking, search, statistical scored search, signal processing, information processing, cryptology, algorithms, formulas, data compression, neural networks, artificial intelligence, Lorentzian fuzzy score, Jaccard'"'"'s coefficient and or Bayesian inference technologies.

6. The method of claim 1, comprised of:

a database, a database management system, an information management system, a knowledge based management system or information exchange, including selective pressure as defined herein, as a filtering or information-processing system.

7. The method of claim 1, comprising:

the Category Rule-Set;

restricting and producing a homogeneous data environment, ensuring uniformity of response(s), to any rule-sets (1-4), or to any query(s), by all data within the Pyramid-Database.

8. The method of claim 1, comprising:

the Category Rule-Set;

wherein the Category database contents are filled by a separate computer program such as, but not limited to the Search-Crawler.

9. The method of claim 1, comprising:

the Category Rule-Set;

wherein the specified database is any freestanding database, accessible or inaccessible from the Internet, including the Internet and/or regardless of the source or type of the information being stored within the database.

10. The method of claim 1, comprising:

the Category Rule-Set;

produces an idealized data-model (map) of the Internet and integrates the real world Internet (web site(s)/page(s), text, objects, and resources) into that idealized map through rational and relational organizational structures, such as, but not limited to the Internet-Category-Data-Model and/or the Link-Cluster Envelope.

11. The method of claim 1, comprising:

the Target Rule-set;

that includes but is not limited to;

any one, any combination of, or all of the following;

text/word/set(s) mapping, text/word/set(s) matching, pattern matching, statistical scoring, ranking, search, statistical scored search, signal processing, information processing, cryptology, algorithms, formulas, data compression, neural networks, artificial intelligence, Lorentzian fuzzy score, Jaccard'"'"'s coefficient and or Bayesian inference technologies;

configured to return an optimized data query result.

12. The method of claim 1, comprising:

the Time Rule-Set;

that ranks, ages, includes, excludes or information processes, utilizing time, day, date, intervals of time, repeated intervals of time or variable intervals of time, or in any other manor provides information-processing utilizing an element of “

Time”

as a component of the Target Rule-Set.

13. The method of claim 1, comprising:

the Time Rule-Set;

that provides for a specific time, number of times, interval or an infinitely variable interval(s) of time(s) to be defined for applying or reapplying rule-sets 1-4.

14. The method of claim 1, comprising:

the Exclusion Rule-Set;

that allows for the determination of the total amount of data that will be modified or returned from the specified database.

15. The method of claim 1, comprising:

the Exclusion Rule-set;

is defined as any number or the calculated result of an algorithm or formula.

16. The method of claim 1, comprising:

the Category Rule-Set;

defining and/or containing dependant catalog b-tree(s) (C1-C7), comprised of list, containing text/word/set, including but not limited to;

categories, subjects, disciplines, classifications and divisions and/or sub-divisions, defining a;

Header Category(s); and

/or Super-Category(s); and

/or Category(s); and

/or Sub-Category(s);

the combined plurality of all categories and there contents, producing the Internet- Category-Data-Model-Header (ICDMH).

17. The method of claim 1, comprising:

the Category Rule-Set;

defining and/or containing all p-value ranked text/word/set(s) inventories, generated as the product of the category-level (C1-C7) searches, incorporating a weighting algorithm or formula upon the final Internet-Category-Data-Model-Body (ICDMB), text/word/set(s) inventories, producing a final Internet-Category-Data-Model-Body text/word/set(s) inventory (C8-C∞

), from the Internet-Category-Data-Model-Header catalogs or text/word/set(s) list.

18. The method of claim 1, comprising:

the Category Rule-Set;

wherein the results of the Internet-Category-Data-Model-Header (C1-C7), information/data, are added to the harvested/collected or fetched Internet-Category-Data-Model-Body (C8-C∞

), information/data, producing a specific, unique, organized categorized and relational Internet-Category-Data-Model (ICDM).

19. The method of claim 1, comprising:

the Category Rule-Set;

appending unique identifying numbers through concatenation of the assigned unique identify numbers associated with each dependant catalog b-tree content list, harvested/fetched Internet-Category-Data-Model-Body text list or randomly generated Header text/word/set(s) list, allowing the unique identification of every Internet-Category-Data-Model-Header or Internet-Category-Data-Model-Body and thus every Internet-Category-Data-Model.

20. The method of claim 1, comprising:

the Category Rule-Set;

wherein a collection of web site(s)/page(s) links have, as a minimum, one other web site(s)/page(s) site/page, linking with it from another site or page, that has a matching Internet-Category-Data-Model (content(s) or ID Log number(s)), thus producing a Link-Cluster-Envelope.

21. The method of claim 1 comprising:

the Category Rule-Set;

defining and/or containing a feedback mechanism wherein the Internet-Category-Data-Model redefines, refreshes and/or updates the Link-Cluster-Envelope and the Link-Cluster-Envelope redefines, refreshes and/or updates the Internet-Category-Data-Model.

22. The method of claim 1, comprising:

the Category Rule-Set;

wherein the IP/URL/URI addresses of all web site(s)/page(s) that match the Internet-Category-Data-Model and have link(s) to or from each other, are defined as the Link-Cluster-Envelope.

23. The method of claim 1, comprising:

the Category Rule-Set;

wherein web site(s)/page(s) site(s) or web site(s)/page(s) page(s) that have the most links to and from them, from within the Link-Cluster-Envelope are stratified, weighted or ranked within the IP/URL/URI log listing.

24. The method of claim 1, comprising:

the Category Rule-Set;

wherein the specified database, is produced and/or contributed to and/or controlled by a Social Network.

25. The method of claim 1, comprising:

the Target Rule-Set;

wherein information processing is accomplished including, but not limited to;

inclusion or exclusion;

elevation or demotion;

null or no action, upon the data within the specified database.

26. A computer program with the combined attributes of a Web Crawler and Search Engine, the “

Search-Crawler”

, wherein it'"'"'s objects are comprising;

1) automatically and systematically produce every permutation of header category-level term combinations (C1-C7), through hierarchal dependant B-tree catalogs and/or randomly, and/or sequentially generated text/word/set(s) lists;

2) conduct an internet search for each category-level term(s) (C1-C7), and produce an optimized and statistically significant text/word/set/inventory from text/word/sets that have been cashed, inventoried and statistically ranked from within the retrieved web site(s)/page(s) for all text sources found within those web site(s)/page(s), for each category level

3) compare and stratify all ranked or scored, text/word/set(s) inventories generated by the category-level searches by a weighting algorithm or formula producing a final body text/word/set, (C8-C∞

), from the Internet-Category-Data-Model-Header contents;

4) the combined Internet-Category-Data-Model-Header information/data, and the Internet-Category-Data-Model-Body information/data, producing the Internet-Category-Data-Model;

5) identify, collect/fetch, rank or stratify by statistical significance and log all IP/URL/URI addresses that fall within the inclusion parameters of the Internet-Category-Data-Model(s);

6) Identify, collect/fetch and log all IP/URL/URI addresses of all web site(s)/page(s) and pages that connect (link) to or from web site(s)/page(s) within the Internet-Category-Data-Model producing a Link-Cluster-Envelope;

7) identify, collect/fetch, link and log all identical web site(s)/page(s) with identical ICDMH and ICDMB contents, without identical IP/URL/URI addresses, and add those links to the Link-Cluster-Envelope;

8) rank or stratify and log or list the link(s) within the Link-Cluster-Envelope with the largest number of outgoing connections (links) within the Link-Cluster-Envelope;

9) rank or stratify and log or list the link(s) with the largest number of incoming connections (links), within the Link-Cluster-Envelope,

10) optimize the ICDM by refreshing the LCE thereby redefining the ICDM;

11) optimize the LCE by refreshing the ICDM, thereby redefining the LCE;

12) to identify and block the production or displaying of any web site(s)/page(s) so designated through any blocking designation technique incorporated within the Search-Crawler,

13) produce a branch tree representation of the links within the ICDM to produce an information/category visual representation or category map of the interconnections of links within the ICDM and/or LCE.

27. The method of claim 27, comprising:

object 2;

determining the occurrence rates and there single or combined statistical significance (P-value) of each text/word/set(s) and/or each web site(s)/page(s), within the Link-Cluster-Envelope as defined by the Internet-Category-Data-Model.

28. The method of claim 27, comprising:

object 3;

determining by statistical analysis the p-value of the occurrences rate of text/word/set(s) within web site(s)/pages(s), thereby determining inclusion or exclusion within the Internet-Category-Data-Model.

29. The method of claim 27, comprising:

a Category Rule-Set;

populated by an internet search-engine, functioning also as a web-crawler and combined with an automatic word-combination generator (all permeations of 2 to 7 word combinations), accomplished sequentially or randomly, wherein the Search-Crawler utilizes the generated word-combinations, instead of Internet-Category-Data-Model-Headers or IP/URL/URI addresses, to map and inventory the internet and populate the Internet-Category-Data-Model-Body.

30. A method for organization and categorization (mapping), web site(s)/page(s), utilizing word(s), groups of words (word-sets), found within the parameters produced by the Internet-Category-Data-Model.