Unit group generation and relationship establishment

1. A non-transitory computer-readable storage medium storing instructions to establish relationships between items, the instructions, when executed by one or more processors, cause the one or more processors to at least:

identify a unit group for a first item, wherein the unit group is identified from a plurality of unit groups including at least one non-random unit group having a joint probability that units of the at least one non-random unit group appearing together is greater than a second probability of the units of the at least one non-random unit group appearing independently;

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;

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

send for display the first item and the second item.

2. The non-transitory computer-readable storage medium of claim 1 , wherein:

the first item includes a first representation; and

the second item includes a second representation, wherein the first representation and the second representation are different from one another.

3. The non-transitory computer-readable storage medium of claim 2 , wherein the unit group is identified for the first item based at least in part on a first annotation.

4. The non-transitory computer-readable storage medium of claim 3 , wherein the first annotation is provided by a first user and is related to a first object that is depicted in the first representation.

5. The non-transitory computer-readable storage medium of claim 4 , wherein:

the unit group is identified for the second item based at least in part on a second annotation that is provided by a second user; and

the second annotation is related to a second object that is depicted in the second representation.

6. The non-transitory computer-readable storage medium of claim 1 , wherein the unit group includes at least one of a character, a word, a symbol, or a number.

7. The non-transitory computer-readable storage medium of claim 1 , wherein the unit group is selected from a plurality of unit groups defined for the corpus of items.

8. The non-transitory computer-readable storage medium of claim 1 , 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.

9. The non-transitory computer-readable storage medium of claim 1 , wherein the relationship is further established based at least in part on the first item and the second item having a same unit group.

10. The non-transitory computer-readable storage medium of claim 1 , wherein the non-transitory computer-readable storage medium stores further instructions that, when executed by the one or more processors, cause the one or more processors to at least determine that the unit group is a non-random unit group.

11. The non-transitory computer-readable storage medium of claim 1 , wherein the non-transitory computer-readable storage medium stores further instructions that, when executed by the one or more processors, cause the one or more processors to at least determine a discount factor for the unit group.

12. A computer-implemented method, comprising:

processing a corpus including a plurality of items to identify unit groups having a first probability of units of the unit group appearing together in the corpus that is greater than a second probability of units of the unit group appearing independently in the corpus in determining a plurality of non-random unit groups;

determining that a first item is associated with a first non-random unit group from the plurality of non-random unit groups;

identifying, from the corpus, a second item that is associated with the first non-random unit group; and

generating a relationship between the first item and the second item.

13. The computer-implemented method of claim 12 , wherein each of the plurality of items of the corpus includes at least one of a representation, an object identifier, a set or a user.

14. The computer-implemented method of claim 12 , wherein each of the plurality of non-random unit groups includes at least two units.

15. The computer-implemented method of claim 12 , further comprising:

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

generating a unit group dictionary that includes the plurality of non-random unit groups and their corresponding discount factors.

16. The computer-implemented method of claim 12 , further comprising:

determining, for each of the plurality of non-random unit groups, a corresponding discount factor based at least in part on a quotient of a frequency of the non-random unit group in the corpus;

comparing, for each of the plurality of non-random unit groups, a corresponding discount factor against a threshold; and

generating a unit group dictionary that includes non-random unit groups from the plurality of non-random unit groups having corresponding discount factors that exceed the threshold.

17. 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 processor to at least:

determine a non-random unit group associated with a first item, the non-random unit group being determined based at least in part on a joint probability associated with at least two units of the non-random unit group that indicates that a first probability that the at least two units of the non-random unit group appearing together in a corpus including a plurality of items is greater than a second probability of the at least two units of the non-random unit group appearing independently;

identify, from the corpus, a second item associated with the non-random unit group; and

send, for presentation on a display, the first item and the second item.

18. The computing system of claim 17 , wherein the program instructions that, when executed by the one or more processors, further cause the one or more processor to at least:

determine a discount factor associated with the non-random unit group, wherein the discount factor is based at least in part on a quotient of a frequency of the non-random unit group in the corpus.