Contextual data mapping, searching and retrieval
First Claim
1. A computer implemented method comprising:
- receiving a first content set, wherein the first content set is organized according to a rules set;
using the rules set to parse the first content set to generate a first pattern set having a plurality of members;
assigning a weighted value to each member of the first and a second pattern set based on a frequency of occurrence of each member in the first and second pattern sets, wherein each member of the first and second pattern sets includes digital content; and
determining a relevancy score linking each of the members of the first and second pattern sets in a one to one mapping of the members of the first pattern set to each of the members of the second pattern set, wherein the relevancy score is based upon the weighted value assigned to each member of the first and second pattern sets and represents a relationship between the members of the first and second pattern sets,wherein determining includes using at least one of a contextual pattern operation;
a structural relationship operation;
a perspective operation;
or combinations thereof; and
wherein assigning a weighted value determining the relevancy score includes applying a formula of Pn=Σ
fipi/n, where;
n is the total number of known patterns in the system;
i is 0 to n;
pi is 1 if the bit pattern or co-related patterns exists; and
f is the fuzziness of a pattern towards another pattern, and wherein determining a relevancy score includes performing a union function on the weighted values.
1 Assignment
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Accused Products
Abstract
An example method is illustrated as including receiving a first content set, the first content set organized according to a rules set, using the rules set to parse the first content set to generate a first pattern set having a plurality of members, assigning a weighted value to each member of the first and a second pattern set based on a frequency of occurrence of each member in the first and second pattern sets, wherein each member of the first and second pattern sets includes digital content, and determining a relevancy score linking each of the members of the first and second pattern set in a one to one mapping of the members of the first pattern set to each of the members of the second pattern set, wherein the relevancy score is based upon the weighted value assigned to each member of the first and second pattern sets.
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Citations
22 Claims
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1. A computer implemented method comprising:
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receiving a first content set, wherein the first content set is organized according to a rules set; using the rules set to parse the first content set to generate a first pattern set having a plurality of members; assigning a weighted value to each member of the first and a second pattern set based on a frequency of occurrence of each member in the first and second pattern sets, wherein each member of the first and second pattern sets includes digital content; and determining a relevancy score linking each of the members of the first and second pattern sets in a one to one mapping of the members of the first pattern set to each of the members of the second pattern set, wherein the relevancy score is based upon the weighted value assigned to each member of the first and second pattern sets and represents a relationship between the members of the first and second pattern sets, wherein determining includes using at least one of a contextual pattern operation;
a structural relationship operation;
a perspective operation;
or combinations thereof; andwherein assigning a weighted value determining the relevancy score includes applying a formula of Pn=Σ
fipi/n, where;
n is the total number of known patterns in the system;
i is 0 to n;
pi is 1 if the bit pattern or co-related patterns exists; and
f is the fuzziness of a pattern towards another pattern, and wherein determining a relevancy score includes performing a union function on the weighted values. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer system comprising:
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a receiver residing on the computer system to receive a first content set and store the first content set in a memory, wherein the first content set is organized according to some rules set; a parser to parse the first content set to generate a first pattern set; an assignor residing on the computer system and including a processor to assign a weighted value to each member of the first and a second pattern sets based on a frequency of occurrence of each member in the first and second pattern sets, wherein each member of the first and second pattern sets includes digital content; a first calculator, including a processor, residing on the computer system to determine a relevancy score linking each of the members of the first and second pattern sets in a one to one mapping of the members of the first pattern set to each of the members of the second pattern set, wherein the relevancy score is based upon the weighted value assigned to each member of the first and second pattern sets and represents a relationship between the members of the first and second pattern sets, wherein the first calculator uses at least one of a contextual pattern operation;
a structural relationship operation;
a perspective operation;
or combinations thereof; andwherein the assignor is to assign the weighted value determining the relevancy score by applying a formula of Pn=Σ
fipi/n, where;
n is the total number of known patterns in the system;
i is 0 to n;
pi is 1 if the bit pattern or co-related patterns exists; and
f is the fuzziness of a pattern towards another pattern, and wherein determining a relevancy score includes performing a union function on the weighted values. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. An apparatus comprising:
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means for receiving a first content set and storing the first content set in a memory, wherein the first content set is organized according to a rules set; means for using the rules set and a processor to parse the first content set to generate a first pattern set having a plurality of members; means for assigning a weighted value to each member of the first and a second pattern set based on a frequency of occurrence of each member in the first and second pattern sets, wherein each member of the first and second pattern sets includes digital content, wherein the means for assigning includes a processor; and means for determining a relevancy score linking each of the members of the first and second pattern sets in a one to one mapping of the members of the first pattern set to each of the members of the second pattern set, wherein the relevancy score is based upon the weighted value assigned to each member of the first and second pattern sets and represents a relationship between the members of the first and second pattern sets, wherein the means for determining includes a processor; wherein the means for assigning a weighted value determining the relevancy score includes means for applying a formula of Pn=Σ
fipi/n, where;
n is the total number of known patterns in the system;
i is 0 to n;
pi is 1 if the bit pattern or co-related patterns exists; and
f is the fuzziness of a pattern towards another pattern, and wherein determining a relevancy score includes performing a union function on the weighted values.
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22. A non-transitory machine-readable storage medium comprising instructions, which when implemented by one or more machines, cause the one or more machines to perform the following operations:
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receive a first content set, wherein the first content set is organized according to a rules set; use the rules set to parse the first content set to generate a first pattern set having a plurality of members; assign a weighted value to each member of the first and a second pattern set based on a frequency of occurrence of each member in the first and second pattern sets, wherein each member of the first and second pattern sets includes digital content; and determine a relevancy score linking each of the members of the first and second pattern set in a one to one mapping of the members of the first pattern set to each of the members of the second pattern set, wherein the relevancy score is based upon the weighted value assigned to each member of the first and second pattern sets and represents a relationship between the members of the first and second pattern sets; wherein the assign operation includes applying a formula of Pn=Σ
fipi/n, where;
n is the total number of known patterns in the system;
i is 0 to n;
pi is 1 if the bit pattern or co-related patterns exists; and
f is the fuzziness of a pattern towards another pattern, and wherein determining a relevancy score includes performing a union function on the weighted values.
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Specification