Measuring and displaying facets in context-based conformed dimensional data gravity wells
First Claim
1. A method of measuring and displaying facets in context-based conformed dimensional data gravity wells, the method comprising:
- receiving, by one or more processors, a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters;
associating, by one or more processors, one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object is a first facet that provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects;
parsing, by one or more processors, the synthetic context-based object into a context-based n-tuple, wherein the context-based n-tuple comprises a pointer to said one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object;
creating, by one or more processors, multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object and at least one context object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells;
calculating, by one or more processors, a virtual mass of a parsed synthetic context-based object, wherein the virtual mass of the parsed synthetic context-based object is derived from a formula of;
Pc(C)×
Wtc(S),where Pc(C) is a probability that the non-contextual data object has been associated with a correct context object, and where Wtc(S) is the weighting factor of importance of the synthetic context-based object;
transmitting, by one or more processors, multiple parsed synthetic context-based objects to the context-based conformed dimensional data gravity wells membrane;
populating, by one or more processors, each of the multiple context-based conformed dimensional data gravity well frameworks with the multiple parsed synthetic context-based objects to define multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object in said particular context-based conformed dimensional data gravity well; and
dynamically adjusting, by one or more processors, a displayed appearance of the particular context-based conformed dimensional data gravity well according to how closely each of the multiple parsed synthetic context-based objects matches said at least one context object.
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Abstract
A processor-implemented method, system, and/or computer program product measures and displays facets in context-based conformed dimensional data gravity wells. Conformed dimensional objects and synthetic context-based objects are parsed into n-tuples. A virtual mass of each parsed object is calculated, in order to define a shape of multiple context-based conformed dimensional data gravity wells that are created when data objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional gravity wells membrane. Data from the multiple context-based conformed dimensional data gravity wells then populates nodes in a data model. A displayed appearance of the particular context-based conformed dimensional data gravity well is dynamically adjusted according to the how closely each of the multiple parsed synthetic context-based objects matches said at least one context object and/or at least one dimension object.
170 Citations
20 Claims
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1. A method of measuring and displaying facets in context-based conformed dimensional data gravity wells, the method comprising:
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receiving, by one or more processors, a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; associating, by one or more processors, one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object is a first facet that provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; parsing, by one or more processors, the synthetic context-based object into a context-based n-tuple, wherein the context-based n-tuple comprises a pointer to said one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; creating, by one or more processors, multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object and at least one context object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; calculating, by one or more processors, a virtual mass of a parsed synthetic context-based object, wherein the virtual mass of the parsed synthetic context-based object is derived from a formula of;
Pc(C)×
Wtc(S),where Pc(C) is a probability that the non-contextual data object has been associated with a correct context object, and where Wtc(S) is the weighting factor of importance of the synthetic context-based object; transmitting, by one or more processors, multiple parsed synthetic context-based objects to the context-based conformed dimensional data gravity wells membrane; populating, by one or more processors, each of the multiple context-based conformed dimensional data gravity well frameworks with the multiple parsed synthetic context-based objects to define multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object in said particular context-based conformed dimensional data gravity well; and dynamically adjusting, by one or more processors, a displayed appearance of the particular context-based conformed dimensional data gravity well according to how closely each of the multiple parsed synthetic context-based objects matches said at least one context object. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
where Pd(C) is a probability that
1) said one of the non-dimensional data objects has been associated with the correct dimensional label,
2) said one of the non-dimensional data objects is uncorrupted, and
3) said one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular dimensional data gravity well; and
where Wtd(S) is the weighting factor of importance of the conformed dimensional object.
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7. The method of claim 5, further comprising:
graphically displaying, by one or more processors, the multiple context-based conformed dimensional data gravity wells according to a combined virtual mass of the multiple parsed synthetic context-based objects and the multiple parsed conformed dimensional objects, wherein a first context-based conformed dimensional data gravity well holds a more virtually massive combination of parsed data objects than a second context-based conformed dimensional data gravity well, and wherein the first context-based conformed dimensional data gravity well extends farther away from the context-based conformed dimensional data gravity wells membrane than the second context-based conformed dimensional data gravity well.
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8. The method of claim 1, wherein a particular data object is either a conformed dimensional object or a synthetic context-based object, the method further comprising:
determining, by one or more processors, a likelihood that the particular data object is pulled into an appropriate context-based conformed dimensional data gravity well according to a Bayesian probability formula of;
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9. The method of claim 1, wherein the weighting factor of importance of the synthetic context-based object is based on how important the synthetic context-based object is to a particular project.
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10. The method of claim 5, further comprising:
determining, by one or more processors, that said one of the non-dimensional data objects is uncorrupted by determining that said one of the non-dimensional data objects is not a fragment of an original data object.
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11. The method of claim 1, further comprising:
graphically representing, by one or more processors, said at least one context object on a wall of said particular context-based conformed dimensional data gravity well.
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12. The method of claim 1, further comprising:
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determining, by one or more processors, an age of each synthetic context-based object that has been pulled into the particular context-based conformed dimensional data gravity well; and removing, by one or more processors, from the particular context-based conformed dimensional data gravity well any data object that is older than a predetermined age.
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13. A computer program product for measuring and displaying facets in context-based conformed dimensional data gravity wells, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable and executable by one or more processors to perform a method comprising:
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receiving a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; associating one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object is a first facet that provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; parsing the synthetic context-based object into a context-based n-tuple, wherein the context-based n-tuple comprises a pointer to said one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; creating multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object and at least one context object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; calculating a virtual mass of a parsed synthetic context-based object, wherein the virtual mass of the parsed synthetic context-based object is derived from a formula of;
Pc(C)×
Wtc(S),where Pc(C) is a probability that the non-contextual data object has been associated with a correct context object, and where Wtc(S) is the weighting factor of importance of the synthetic context-based object; transmitting multiple parsed synthetic context-based objects to the context-based conformed dimensional data gravity wells membrane; populating each of the multiple context-based conformed dimensional data gravity well frameworks with the multiple parsed synthetic context-based objects to define multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object in said particular context-based conformed dimensional data gravity well; and dynamically adjusting a displayed appearance of the particular context-based conformed dimensional data gravity well according to how closely each of the multiple parsed synthetic context-based objects matches said at least one context object. - View Dependent Claims (14, 15, 16, 17)
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18. A computer system comprising:
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a processor, a computer readable memory, and a computer readable storage medium; first program instructions to receive a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; second program instructions to associate one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object is a first facet that provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; third program instructions to parse the synthetic context-based object into a context-based n-tuple, wherein the context-based n-tuple comprises a pointer to said one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; fourth program instructions create multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object and at least one context object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; fifth program instructions to calculate a virtual mass of a parsed synthetic context-based object, wherein the virtual mass of the parsed synthetic context-based object is derived from a formula of;
Pc(C)×
Wtc(S),where Pc(C) is a probability that the non-contextual data object has been associated with a correct context object, and where Wtc(S) is the weighting factor of importance of the synthetic context-based object; sixth program instructions to transmit multiple parsed synthetic context-based objects to the context-based conformed dimensional data gravity wells membrane; seventh program instructions to populate each of the multiple context-based conformed dimensional data gravity well frameworks with the multiple parsed synthetic context-based objects to define multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object in said particular context-based conformed dimensional data gravity well; and eighth program instructions to dynamically adjust a displayed appearance of the particular context-based conformed dimensional data gravity well according to how closely each of the multiple parsed synthetic context-based objects matches said at least one context object; and
wherein;the first, second, third, fourth, fifth, sixth, seventh, and eighth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. - View Dependent Claims (19, 20)
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Specification