Unit group generation and relationship establishment

1. A computer-implemented method, comprising:

under control of one or more computing systems configured with executable instructions,

identifying a corpus of items, wherein a plurality of the corpus of items include annotations;

processing the annotations to identify a plurality of non-random unit groups;

for each of the plurality of non-random unit groups, determining a discount factor based at least in part on a quotient of a number of times the non-random unit group appears in the corpus and a number of items in the corpus; and

generating a unit group dictionary that includes non-random unit groups with a discount factor above a defined threshold.

2. The computer-implemented method of claim 1 , wherein each of the plurality of non-random unit groups include at least two units.

3. The computer-implemented method of claim 2 , wherein each of the plurality of non-random unit groups are identified based at least in part on a probability that the at least two units of the unit group appearing together in the corpus is greater than a probability of the at least two units of the unit group appearing independently in the corpus.

4. The computer-implemented method of claim 1 , wherein the items include at least one of a representation, an object identifier, a set, or a user.

5. The computer-implemented method of claim 1 , wherein a non-random unit group is identified in the annotations based at least in part on a probability that units of the unit group appear together in the corpus is greater than a probability of the units appearing separately in the corpus.

6. The computer-implemented method of claim 1 , wherein the units include at least one of a character, a word, a symbol, or a number.

7. The computer-implemented method of claim 1 , wherein the corpus includes all items managed by an object management service.

8. The computer-implemented method of claim 1 , wherein the discount factor is a log of the quotient.

9. A non-transitory computer-readable storage medium storing instructions to establish relationships between items, the instructions when executed by a processor causing the processor to at least:

identify a unit group for a first item, wherein the unit group is established based at least in part on a user provided annotation;

identify a second item of a corpus of items having the unit group associated therewith;

establish a relationship between the first item and the second item based at least in part on the unit group;

determine a discount factor for the unit group based at least in part on a quotient of a frequency of the unit group in a corpus and a number of items in the corpus;

receive a request from a computing device to view the first item;

and

send for display the first item and the second item.

10. The non-transitory computer-readable storage medium of claim 9 , wherein the discount factor is a log of the quotient.

11. The non-transitory computer-readable storage medium of claim 9 , wherein the unit group includes at least one of a character, a word, a symbol or a number.

12. The non-transitory computer-readable storage medium of claim 9 , wherein the unit group is selected from a plurality of unit groups defined for the corpus.

13. The non-transitory computer-readable storage medium of claim 9 , wherein the unit group for the first item is identified based on a selection of a unit group from a plurality of unit groups associated with the first item.

14. The non-transitory computer-readable storage medium of claim 9 , wherein the relationship is further established based at least in part on the first item and the second item having a same unit group.

15. A computing system, comprising:

one or more processors; and

a memory coupled to the one or more processors and storing program instructions that when executed by the one or more processors cause the one or more processors to:

identify a corpus including a plurality of items, wherein each of the plurality of items include associated annotations;

process the associated annotations to identify a first plurality of non-random unit groups, wherein each non-random unit group includes at least two units included in the associated annotations;

for each non-random unit group of the first plurality of non-random unit groups, generate a discount factor based at least in part on a quotient of a frequency of the unit group in the corpus and a number of the plurality of items in the corpus; and

generate a dictionary of a second plurality of non-random unit groups identified from the first plurality of non-random unit groups.

16. The computing system of claim 15 , wherein each of the first plurality of non-random unit groups are determined based on a joint probability that the at least two units of the unit group appearing together in the corpus is greater than a probability of the at least two units of the unit group appearing independently in the corpus.

17. The computing system of claim 16 , wherein the joint probability is determined based at least in part on a number of times the at least two units of the unit group appear together in the corpus.

18. The computing system of claim 16 , wherein the probability is determined based at least in part on a number of times the at least two units of the unit group appear independently in the corpus.

19. The computing system of claim 15 , wherein the discount factor is a log of the quotient.

20. The computing system of claim 15 , wherein the corpus includes all items managed by an object management service.