Determining a relative importance among ordered lists

1. A method, comprising:

determining, on a computing device, total distances between two or more ordered lists, wherein a given total distance is associated with a given ordered list and is determined between the given ordered list and others of the two or more ordered lists;

associating one or more importance factors with at least one of the two or more ordered lists, wherein a given importance factor associated with the given ordered list is based at least in part on the determined total distances;

generating an importance vector based at least in part upon the associated one or more importance factors; and

determining a consensus ordered list based at least in part upon the two or more ordered lists and an optimization of the importance vector via an optimization tool.

2. The method of claim 1 , wherein the given total distance is determined between the given ordered list and all of the other two or more ordered lists.

3. The method of claim 1 , wherein the total distances are determined based at least in part on Kendall tau distances or Spearman's footrule distances.

4. The method of claim 1 , wherein the two or more ordered lists individually include a plurality of ordered elements.

5. The method of claim 1 , wherein the two or more ordered lists individually include a plurality of ordered elements, and wherein the given total distance is determined between the plurality of ordered elements associated with the given ordered list and the plurality of ordered elements associated with all of the other two or more ordered lists.

6. The method of claim 1 , wherein the determining the total distances, the associating the one or more importance factors, and the determining the consensus ordered list are performed in an unsupervised manner.

7. The method of claim 1 , wherein the two or more ordered lists include one or more following information types: an ordered list of items responsive to a search query, an ordered list of genes, and an ordered list of items relevant to a purchase decision.

8. The method of claim 1 , wherein the determining the consensus ordered list includes:

determining two or more potential consensus ordered lists, wherein a given ordered list is determined based at least in part upon minimizing a total distance between the given potential ordered list and the two or more ordered lists; and

minimizing an objective function based at least in part upon the importance vector, the two or more potential consensus ordered lists, the two or more ordered lists, and the determined total distances.

9. The method of claim 8 , wherein the determining the two or more potential consensus ordered lists includes:

minimizing the total distance between a given ordered list and the two or more ordered lists based at least in part upon application of a genetic algorithm or a cross-entropy Monte Carlo analysis.

10. A method, comprising:

obtaining two or more ordered lists, wherein the two or more ordered lists are ranked search results generated in response to a query;

determining total distances between the two or more ordered lists, wherein a given total distance is associated with a given ordered list and is determined between the given ordered list and others of the two or more ordered lists;

associating one or more importance factors with at least one of the two or more ordered lists, wherein a given importance factor associated with the given ordered list is based at least in part on the determined total distances;

generating an importance vector based at least in part upon the associated one or more importance factors;

determining a consensus ordered list based at least in part on an analysis of the two or more ordered lists and the importance vector via an optimization tool; and

transmitting the consensus ordered list in response to the query.

11. The method of claim 10 , wherein the given total distance is determined between the given ordered list and all of the other two or more ordered lists, and wherein the total distances are determined based at least in part on Kendall tau distances or Spearman's footrule distances.

12. The method of claim 10 , wherein the two or more ordered lists individually include a plurality of ordered elements, and wherein the given total distance is determined between the plurality of ordered elements associated with the given ordered list and the plurality of ordered elements associated with all of the other two or more ordered lists.

13. The method of claim 10 , wherein the determining the total distances, the associating the one or more importance factors, and the determining the consensus ordered list are performed in an unsupervised manner.

14. The method of claim 10 , wherein the determining the consensus ordered list includes:

determining two or more potential consensus ordered lists, wherein a given ordered list is determined based at least in part upon minimizing a total distance between the given potential ordered list and the two or more ordered lists; and

minimizing an objective function based at least in part upon the importance vector, the two or more potential consensus ordered lists, the two or more ordered lists, and the determined total distances.

15. A computing device comprising:

a processor; and

a memory operatively associated with the processor, the memory having machine-readable instructions stored thereon, which, when executed by the processor, operatively enable the computing device to:

obtain two or more ordered lists, wherein the two or more ordered lists are ranked search results generated in response to a query;

determine total distances between the two or more ordered lists, wherein a given total distance is associated with a given ordered list and is determined between the given ordered list and others of the two or more ordered lists;

associate one or more importance factors with at least one of the two or more ordered lists, wherein a given importance factor associated with the given ordered list is based at least in part on the determined total distances;

generate an importance vector based at least in part upon the associated one or more associated importance factors;

determine a consensus ordered list based at least in part on an analysis of the two or more ordered lists and the importance vector via an optimization tool; and

transmit the consensus ordered list in response to the query.

16. The computing device of claim 15 , wherein the given total distance is determined between the given ordered list and all of the other two or more ordered lists, and wherein the total distances are determined based at least in part on Kendall tau distances or Spearman's footrule distances.

17. The computing device of claim 15 , wherein the two or more ordered lists individually include a plurality of ordered elements, and wherein the given total distance is determined between the plurality of ordered elements associated with the given ordered list and the plurality of ordered elements associated with all of the other two or more ordered lists.

18. The computing device of claim 15 , wherein the determination of the total distances, the association of the one or more importance factors, and the determination of the consensus ordered list are performed in an unsupervised manner.

19. The apparatus of claim 15 , wherein the machine-readable instructions further operatively enable the computing device to:

determine two or more potential consensus ordered lists, wherein a given ordered list is determined based at least in part upon minimizing a total distance between the given potential ordered list and the two or more ordered lists; and

minimize an objective function based at least in part upon the importance vector, the two or more potential consensus ordered lists, the two or more ordered lists, and the determined total distances.

20. An article comprising:

a non-transitory signal bearing medium comprising machine-readable instructions stored thereon, which, when executed by one or more processors, operatively enable a computing device to:

obtain two or more ordered lists, wherein the two or more ordered lists are ranked search results generated in response to a query;

determine total distances between the two or more ordered lists, wherein a given total distance is determined between a given ordered list and others of the two or more ordered lists;

associate one or more importance factors to at least one of the two or more ordered lists, wherein a given importance factor associated with the given ordered list is based at least in part on the determined total distances;

generate an importance vector based at in part upon the associated one or more importance factors;

determine a consensus ordered list based at least in part on an analysis of the two or more ordered lists and the importance vector via an optimization tool; and

transmit the consensus ordered list in response to the query.

21. The article of claim 20 , wherein the given total distance is determined between the given ordered list and all of the other two or more ordered lists, and wherein the total distances are determined based at least in part on Kendall tau distances or Spearman's footrule distances.

22. The article of claim 20 , wherein the two or more ordered lists individually include a plurality of ordered elements, and wherein the given total distance is determined between the plurality of ordered elements associated with the given ordered list and the plurality of ordered elements associated with all of the other two or more ordered lists.

23. The article of claim 20 , wherein the determination of the total distances, the association of the one or more importance factors, and the determination of the consensus ordered list are performed in an unsupervised manner.

24. The article of claim 20 , wherein the machine-readable instructions further operatively enable the computing device to:

determine two or more potential consensus ordered lists, wherein a given ordered list is determined based at least in part upon minimizing a total distance between the given potential ordered list and the two or more ordered lists; and

minimize an objective function based at least in part upon the importance vector, the two or more potential consensus ordered lists, the two or more ordered lists, and the determined total distances.