Systems, devices, and/or methods for managing sample selection bias
View Patent ↗Certain exemplary embodiments can provide a method that can include, via a special purpose processor, automatically determining an unbiased estimate of a distribution from occurrence data having an occurrence data sample selection bias substantially equivalent to a background data sample selection bias, the occurrence data related to background data, the background data chosen with the background data sample selection bias, the occurrence data representing a physically-measurable variable of one or more physical and tangible objects or substances.
1. A system for managing sample selection bias, comprising;
a memory that stores instructions; and
a processor that executes the instructions to perform operations, the operations comprising:
randomly selecting sentences in a source language to obtain background data, wherein the background data has a background data sample selection bias that is equivalent to an occurrence data sample selection bias of occurrence data;
sampling sentences in the source language that contain a predetermined word to obtain the occurrence data, wherein the predetermined word is contained in translations of the sentences sampled in the source language; and
determining an unbiased estimate of a distribution utilized for language translation from the occurrence data, wherein the occurrence data is related to the background data.
2. The system of claim 1 , wherein the operations further comprise selecting the background data such that the background data and the occurrence data have equivalent environmental biases.
3. The system of claim 1 , wherein the operations further comprising determining a set of constraints that the distribution satisfies.
4. The system of claim 3 , wherein the operations further comprise determining a distribution of maximum entropy that is subject to the set of constraints.
5. The system of claim 1 , wherein the operations further comprise determining parameters that minimize a penalty function and maximize a likelihood of the background data.
6. The system of claim 1 , wherein the operations further comprise determining the unbiased estimate by utilizing a regression technique.
7. The system of claim 1 , wherein the unbiased estimate of the distribution is further utilized for speech interpretation.
8. The system of claim 1 , wherein the occurrence data represents a physically-measurable variable of a physical and tangible object, and a physical and tangible substance.
9. The system of claim 1 , wherein the operations further comprise rendering a symbol that represents the unbiased estimate of the distribution via an interface.
10. A method for managing sample selection bias, comprising;
randomly selecting sentences in a source language to obtain background data, wherein the background data has a background data sample selection bias that is equivalent to an occurrence data sample selection bias of occurrence data;
sampling sentences in the source language that contain a predetermined word to obtain the occurrence data, wherein the predetermined word is contained in translations of the sentences sampled in the source language; and
determining an unbiased estimate of a distribution utilized for speech interpretation from the occurrence data by utilizing instructions stored in memory and executed by a processor, wherein the occurrence data is related to the background data.
11. The method of claim 10 , further comprising rendering a symbol that represents the unbiased estimate of the distribution via an interface.
12. The method of claim 10 , further comprising selecting the background data such that the background data and the occurrence data have environmental biases that are the same.
13. The method of claim 10 , wherein the unbiased estimate of the distribution is further utilized for language translation.
14. The method of claim 10 , further comprising determining parameters that minimize a penalty function and maximize a likelihood of the background data.
15. The method of claim 10 , further comprising determining a set of constraints that the distribution satisfies.
16. The method of claim 15 , further comprising determining a distribution of maximum entropy that is subject to the set of constraints.
17. The method of claim 10 , further comprising randomly selecting the sentences and sampling the sentences at a selected node of a network.
18. A computer-readable device comprising instructions, which when executed by a processor, cause the processor to perform operations comprising:
randomly selecting sentences in a source language to obtain background data, wherein the background data has a background data sample selection bias that is equivalent to an occurrence data sample selection bias of occurrence data;
sampling sentences in the source language that contain a predetermined word to obtain the occurrence data, wherein the predetermined word is contained in translations of the sentences sampled in the source language; and
determining an unbiased estimate of a distribution from the occurrence data, wherein the occurrence data is related to the background data.