Multi-magnitudinal vectors with resolution based on source vector features

1. A non-transitory computer readable medium encoded with instructions executable by a processor of a computing system for performing vector comparison in natural language processing, the instructions comprising instructions for:

receiving a target vector and a source vector, the target vector including a first target vector dimension comprising a first word or phrase and a second target vector dimension comprising a second word or phrase;

assigning a first magnitude comprising a first weight to the first target vector dimension based on a first feature associated with the source vector;

assigning a second magnitude comprising a second weight to the second target vector dimension based on a second feature associated with the source vector;

determining a total number of dimensions present in the target vector; and

determining whether a current dimension of the target vector is a last dimension to be processed.

2. The non-transitory computer readable medium of claim 1 , wherein the instructions further comprise instructions for:

comparing the target vector with the source vector to obtain a similarity measure by measuring an angle between the target vector and the source vector.

3. The non-transitory computer readable medium of claim 1 , wherein the instructions further comprise instructions for:

storing the source vector in a source data storage memory; and

storing the target vector in a semantic data storage memory.

4. The non-transitory computer readable medium of claim 1 , wherein the source vector is created by a parser from one or more source documents.

5. The non-transitory computer readable medium of claim 1 , wherein the first feature or the second feature associated with the source vector comprises a morphological characteristic, a syntax, a proximity to one or more additional terms or phrases associated with the source vector, a frequency, a date or a time, a location, an origination location of a source document, an event location, a source document analysis location, or a purpose for which the vector comparison is occurring.

6. The non-transitory computer readable medium of claim 1 , wherein assigning a low weight to the first or second magnitude cannot prevent a match between the target vector and the source vector.

7. The non-transitory computer readable medium of claim 1 , wherein the instructions further comprise instructions for:

determining whether a source vector dimension has more than one possible magnitude, wherein the magnitude comprises a weight.

8. A system for performing vector comparison in natural language processing, the system comprising at least one processing unit coupled to a memory, wherein the memory is encoded with computer executable instructions that, when executed, cause the at least one processing unit to:

receive a target vector and a source vector, the target vector including a first target vector dimension comprising a first word or phrase and a second target vector dimension comprising a second word or phrase;

assign a first magnitude comprising a first weight to the first target vector dimension based on a first feature associated with the source vector;

assign a second magnitude comprising a second weight to the second target vector dimension based on a second feature associated with the source vector;

determine a total number of dimensions present in the target vector; and

determine whether a current dimension of the target vector is a last dimension to be processed.

9. The system of claim 8 , wherein the instructions further cause the at least one processing unit to:

compare the target vector with the source vector to obtain a similarity measure by measuring an angle between the target vector and the source vector.

10. The system of claim 9 , wherein an order of the first word or phrase and an order of the second word for phrase do not impact the similarity measure.

11. The system of claim 8 , wherein the memory comprises:

a source data storage memory configured to store the source vector; and

a semantic data storage memory configured to store the target vector.

12. The system of claim 8 , wherein the source vector is created by a parser from one or more source documents.

13. The system of claim 8 , wherein the first feature or the second feature associated with the source vector comprises a morphological characteristic, a syntax, a proximity to one or more additional terms or phrases associated with the source vector, a frequency, a date or a time, a location, an origination location of a source document, an event location, a source document analysis location, or a purpose for which the vector comparison is occurring.

14. The system of claim 8 , wherein the instructions further cause the at least one processing unit to:

if the first or second magnitude comprises a low weight, match the target vector to the source vector even if the first or second magnitude does not match the first or second feature associated with the source vector.

15. The system of claim 8 , wherein the instructions further cause the at least one processing unit to:

determine whether a source vector dimension has more than one possible magnitude, wherein the magnitude comprises a weight.

16. The system of claim 8 , wherein the first magnitude and the second magnitude are each associated with a respective indexed data structure.