Search engine optimizer

• US 8,868,535 B1
• Filed: 09/28/2011
• Issued: 10/21/2014
• Est. Priority Date: 02/24/2000
• Status: Expired due to Fees

• Current Assignee: Richard Paiz
• Original Assignee: Richard Paiz
• Inventors: Paiz, Richard
• Primary Examiner(s): SOMERS, MARC S
• Application Number:
  US13/247,964
• Time in Patent Office: 1,119 Days
• Field of Search: 707/711, 707/741, 707/736, 707/706, 707/705
• US Class Current: 707/706
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

A method of executing a word search on a computer with a software program mimicking the human brain by adding knowledge, understanding and wisdom to simulate deductive reasoning to create a language based equation and a geospatial based equation includes the steps of assigning a unique value from lowest to highest to lowest; organizing and distributing the Internet environment into quality partitions from lowest to highest establishing a glyph database; processing the impact of a managerial hierarchical related group of index relationships to create an equation that shrinks the search environment; organizing and distributing the Internet using human brain tendencies; and modifying each the request by: identifying for each static and dynamic request the best suited search pattern within the search pattern database and automatically sending the preprocessed results to the end of a user'"'"'s browser as output.

Claims

1. A method of executing a word search on a computer with a software program to buffer between an Internet browser and a search engine to interpret numerical and text data and convert the interpreted data into a search pattern, wherein software program establishes a search pattern database, via a server which a set of software instructions and upon finding a match sends the output in response to the end user valid request, the methods comprising the steps of:

a. assigning a unique value from lowest to highest to each site and web page;

b. establishing a pattern database means with a collection of all hierarchical index relationships wherein pattern database executes software instructions employing set theory constructs to process the impact of each exact search pattern to create a probabilistic spatial environment and selecting as output the highest valued web pages;

c. establishing a glyph database means with a collection of all keywords and clusters based on language;

wherein glyph database executes software instructions to interpret numerical and text data and convert the interpreted data into an exact search pattern;

d. executing a set of software instructions to search the pattern database in order to identify said exact search pattern, via a server which executes a set of software instructions and upon finding an match automatically sending the preprocessed calculated results to the end user'"'"'s browser as output.

2. A method of executing a word search on a computer with a software program mimicking the human brain by adding knowledge, wisdom and understanding to simulate deductive reasoning to create a language based equation and a geospatial based equation to buffer between an Internet browser and a search engine to interpret numerical and text data and convert the interpreted data into statistical glyphs objects representing the mathematical equation used to determine an optimal partition of the Internet, and then employs a search strategy to find and supply missing gaps of information, and dynamically valorizes, reorganizes, commercializes and measures end user'"'"'s satisfaction, and hierarchically prioritizes said statistical glyph objects as a search pattern used to obtain an optimal match in response to an end user valid request, the methods comprising the steps of:

a. assigning a probabilistic value from lowest to highest to each site and web page;

b. establishing a pattern database means with a collection of all hierarchical index relationships wherein pattern database executes software instructions employing fuzzy set theory constructs to process the impact of each probable search pattern to create a probabilistic spatial environment;

c. organizing the Internet into a hierarchical set, using the pattern database, executing informatics constructs to create super blocks based on language;

d. wherein applying fuzzy set theory constructs to partition each super block into blocks using primary index relationships and each block into sub blocks using secondary index relationships and each sub block into mini blocks using tertiary index relationships; and

probabilistically filtering relevant pages using index relationships;

e. indexing an improved environment of each partition of said hierarchical set based on the probable value of each web page and then selecting as output the highest valued web pages;

f. establishing a glyph database means with a collection of all keywords and clusters based on language;

wherein glyph database executes software instructions to interactively interpret numerical and text data and convert the interpreted data into a probable search pattern;

g. correlating a plurality of probabilistic spatial environments based on said probable search pattern, and executing a set of software instructions to search the pattern database in order to identify said probable search pattern, and upon finding a match, performing a cherry picking process by reading, parsing, and analyzing in behalf of the end user word by word each sentence and web page to create the best answer and then sending the preprocessed said best answer to the end user'"'"'s browser as output.

3. A method of executing a word search on a computer with a software program mimicking the human brain by adding knowledge, wisdom and understanding to simulate deductive reasoning to create a language based equation and a geospatial based equation to buffer between an Internet browser and a search engine to interpret numerical and text data and convert the interpreted data into statistical glyphs objects representing the mathematical equation used to determine an optimal partition of the Internet, and then employs a search strategy to find and supply missing gaps of information, and dynamically valorizes, reorganizes, commercializes and measures end user'"'"'s satisfaction, and hierarchically prioritizes said statistical glyph objects as a search pattern used to obtain an optimal match in response to an end user valid request, the methods comprising the steps of:

a. assigning a unique value from lowest to highest to each site and web page;

b. establishing a pattern database means with a collection of all hierarchical index relationships wherein pattern database executes software instructions employing set theory constructs to process the impact of each valid search pattern to create a probabilistic spatial environment;

c. organizing and distributing the Internet into a hierarchical set, using the pattern database, performing a set of software instructions to create a plurality of super blocks; and

applying set theory constructs to partition each super block into blocks using primary index relationships; and

each block into sub blocks using secondary index relationships; and

each sub block into mini blocks using tertiary index relationships; and

filtering relevant pages using index relationships;

d. correlating at least one probabilistic spatial environment to map an improved environment;

e. indexing each said improved environment of said hierarchical set based on the unique value of each web page and then selecting as output the highest valued web pages;

f. establishing a glyph database means with a collection of all keywords and clusters;

wherein glyph database executes software instructions using a search strategy to interpret numerical and text data and convert the interpreted data into a valid search pattern; and

g. executing a set of software instructions to search the pattern database in order to identify said valid search pattern, and upon finding a match automatically sending the preprocessed calculated results to the end user'"'"'s browser as output.

4. The method of claim 3, further comprising the step of scanning each request and determining based on the quality of the keyword combination whether at least one superset (i), secondary set (i, j), and tertiary subset (i, j, k) of the partitions exists in the pattern database, and thus having readily available and preprocessed the optimal response, requiring no further calculations, bypassing the usage of existing search engine capabilities.

5. A method of executing a word search on a computer with a software program mimicking the human brain by adding knowledge, understanding and wisdom to simulate deductive reasoning to create a language based equation and a geospatial based equation to buffer between an Internet browser and a search engine to interpret numerical and text data and convert the interpreted data into statistical glyphs objects representing the mathematical equation used to determine the optimal partition of the Internet, and then find and supply missing gaps of information, and which dynamically valorizes, reorganizes, commercializes, measures end user'"'"'s satisfaction, and then hierarchically prioritizes said statistical glyphs objects as a search pattern used to obtain an optimal match in response to an end user valid request, the method comprising the steps of:

a. assigning a unique value from lowest to highest to each site and web page;

b. organizing the Internet environment into quality partitions from lowest to highest establishing a glyph database means with a collection of all keywords and clusters;

c. establishing a search pattern database means with a collection of all hierarchical index relationships;

d. processing the impact of a managerial hierarchical related group of index relationships to create an equation that shrinks the size of the search environment by purifying the search process by using a primary, secondary and tertiary index relationships;

e. correlating a plurality of spatial environments to map an improved probabilistic environment;

f. distributing the Internet environment using human brain tendencies into a plurality of super blocks;

g. restricting relevant pages within each super block using the primary index relationship into blocks;

h. dividing each block using the secondary index relationship into sub blocks;

i. subdividing each sub-block using the tertiary index relationship into mini blocks;

j. dissecting each mini block into individual elements;

j. assigning to each request a dominant tendency of the brain and anchor glyph that yields the destination;

k. synergistically combining for each request the dominant tendency of the brain and the anchor glyph to select a search strategy that creates a managerial hierarchical set; and

l. modifying each said request by identifying for each static and dynamic request the best suited search pattern within said search pattern database and automatically sending the preprocessed calculated results to the end of a user'"'"'s browser as output.

6. The method of claim 5, comprising an additional step of identifying key words and clusters that confound and restrict the search as zero cluster glyphs.

7. The method of claim 6, comprising an additional step of assigning a vector magnitude to each statistical glyphs objects based on frequency of occurrence from lowest to highest.

8. The method of claim 7, comprising the additional step of defining a series of environment domains;

and

applying site quality filters to select the highest valued site and pages within each environment domain of the series of environment domains.

9. The method of claim 8, comprising an additional step of mapping each search pattern into a managerial hierarchical set.

10. The method of claim 9, comprising an additional step of permitting at least one significant request to belong to a session.

11. The method of claim 10, comprising an additional step of grouping static request glyph values into dynamic session glyph values.

12. The method of claim 11, comprising an additional step of maximizing and minimizing said dynamic session glyphs values based on end user usage patterns of behavior.

13. The method of claim 12, comprising an additional step of solving for missing gaps of information that improve the session.

14. The method of claim 5, comprising an additional step of modifying each search request by transforming each request into a vague search that maps, plots and probabilistically traces each page of the Internet into a super block using the search strategy to create a relevant environment that eliminates from calculation any web page that does not belong to the super block and then ranks and stores each web page of the super block from the lowest to the highest within the managerial hierarchical set.

15. The method of claim 14, comprising an additional steps of:

modifying each search request by transforming each vague search into a concise search that maps, plots and probabilistically traces each page of said super block into a block using the primary index relationship to create an improved environment that eliminates from calculation any web page that does not belong to the block and then ranks and stores each web page of the block from lowest to highest within a superset;

analyzing for each block a selected number of top links information to derive human knowledge by measuring the primary index relationship to find a first group of key featured associations and then solving for missing gaps of information to expand the glyph equation, which by default is the top links; and

eliminating the primary index relationship from further filtering.

16. The method of claim 15, comprising additional steps of:

modifying each search request by transforming each concise search into a precise search that maps, plots and probabilistically traces each page of the blocks into a sub block using the secondary index relationship to create an optimal environment that eliminates from calculation any web page that does not belong to the sub block and then ranks and stores each web page of the sub block from lowest to highest within a set;

and performing human wisdom analysis by correlating the top paragraph reference sources of each index relationship of said sub block to find the second group of key featured associations to expand the glyph equation; and

eliminating the secondary index relationship from further filtering.

17. The method of claim 16, comprising an additional steps of:

modifying each search

request by transforming each precise search into an optimal search that maps, plots and probabilistically traces each page of the sub block into a mini block using the tertiary index relationship to create an optimal solution that eliminates from calculation any web page that does not belong to the mini block and then ranks and stores each web page of the mini block from lowest to highest within a subset; and

adding human understanding by analyzing each page within each partial environment based on trending of the mini blocks to find the third group of key featured associations to expand the glyph equation; and

eliminating the tertiary index relationship from further filtering.

18. The method of claim 17, comprising an additional steps of:

modifying the each search request by performing a cherry picking process by reading, parsing and analyzing on behalf of the end user word by word each sentence, paragraph and web page to create the best answer, of the mini block making exact comparison of the end user'"'"'s typed glyphs and the key featured associations and the missing gaps of information obtained while changing the vague search into an optimal search; and

assigning to each page a deductive reasoning content score based on trending that is added to the inductive reasoning popularity and commercial scores to derive the final value; and

picking the highest final valued page as the best answer and then using the final value to sort the pages of the mini block in ascending order and send a selected top number of pages to the end user'"'"'s browser as output;

default ranking and sorting each page belonging to each partition of the Internet from highest to lowest.

19. The method of claim 18, comprising an additional steps of:

storing each page belonging to each partition and then creating a partial master index that maps each data set.

20. The method of claim 19, comprising an additional step of combining a plurality of consecutive related requests into a dynamic request by altering each statistical glyphs object, page and site, into a super glyph, super page and super site, with multiple popularity and content score values based on trending.

21. The method of claim 20, comprising an additional step of instantiating new search patterns not found in the search pattern database by creating a managerial hierarchical data set to obtain answer and store the information in said search pattern database.

22. The method of claim 14, comprising additional steps of:

distributing the Internet using human brain tendencies into a plurality of super blocks to create a relevant environment that eliminates from calculation any web page that does not belong to the super block and then ranks and stores each web page of super block from lowest to highest within said managerial hierarchical data set;

each vague search creating a super block that maps a relevant environment with the lowest information certainty value;

each super block becoming a join pyramid object that uses rules of semantics and English grammar and search strategy business rules to rank, probabilistically map and index each page belonging to the join pyramid into a managerial hierarchical set that is stored in the join pyramid partial master index.

23. The method of claim 22, comprising an additional step of restricting relevant pages within each super block into blocks using the primary index relationship to create an improved environment that eliminates from calculation any web page that does not belong to the block and then ranks and stores each web page of the block from lowest to highest within a superset, such that each concise search creates a block which maps an improved environment with the second information certainty value, and each block becomes a simple pyramid object by adding first key featured associations and filters the relevant environment using the primary index relationship and then ranks, probabilistically maps and indexes each page belonging to the simple pyramid into a superset data set that is stored in the simple pyramid partial master index.

24. The method of claim 23, comprising an additional step of dividing each block into sub blocks using the secondary index relationship to create an optimal environment that eliminates from calculation any web page that does not belong to the sub block and then ranks and stores each web page of the sub block from lowest to highest into a set, such that each precise search creates a sub block that maps an optimal environment with the third information certainty value, and such that each sub block becomes a hybrid pyramid object by adding second key featured associations and filters the improved environment using the secondary index relationship and then ranks, probabilistically maps and indexes each page belonging to the hybrid pyramid into the set data set that is stored in the hybrid pyramid partial master index.

25. The method of claim 24, comprising an additional step of subdividing each sub block into mini blocks using the tertiary index relationship into sub blocks to create an optimal environment that eliminates from calculation any web page that does not belong to the mini block and then ranks and stores each web page of the mini block from lowest to highest into a subset, such that each optimal search creates a mini block that maps an optimal solution with the fourth information certainty value and contains 100 web pages, and such that each mini block becomes a complex pyramid object by adding third key featured associations and filters the optimal environment using the tertiary index relationship and then ranks, probabilistically maps and indexes each page belonging to the complex pyramid into the subset data set that is stored in the complex pyramid partial master index.

26. The method of claim 25, comprising an additional step of performing the cherry picking process by reading, parsing and analyzing on behalf of an end user word by word each sentence and web page of the mini block making exact comparison of the end user typed glyphs and the key featured associations and the missing gaps of information obtained while changing the vague search into an optimal search, such that each answer search creates an element that maps the final destination and has the highest information certainty value;

such that each element becomes an optimal pyramid and selects the top web pages of the optimal solution by assigning to each page a deductive reasoning content score that is added to the inductive reasoning popularity and commercial scores to derive the final value and then selects the highest final valued page as the best answer and the remaining web pages in ascending order and sends the top pages to the end user browser as output which by default is 10.

27. The method of claim 5, comprising an additional step of using valid super glyph parameters to identify a valid vague search within the search pattern database in order to expand the glyph equation.

28. The method of claim 27, comprising an additional step of using valid super glyph parameters to identify a valid concise search within the search pattern database in order to expand the glyph equation.

29. The method of claim 28, comprising an additional step of using the valid super glyph parameters to identify a valid precise search within the search pattern database in order to expand the glyph equation.

30. The method of claim 29, comprising an additional step of using valid super glyph parameters to identify a valid optimal search within the search pattern database in order to expand the glyph equation.

31. The method of claim 30, comprising an additional step of using valid super glyph parameters to identify an answer search within the search pattern database and then sending the preprocessed top pages as output.

32. The method of claim 31, comprising an additional step of updating existing search patterns at incipiency as web crawlers detect significant difference changes in the environment and the updating with the latest information each managerial hierarchical set and the corresponding partial master indices of the chain of command in real time.