Systems for suggesting content components

1. In a digital medium environment, a method implemented by a computing device, the method comprising:

extracting, by a document object model (DOM) module, a content component included in a hypertext markup language (HTML) document;

representing, by the DOM module, a feature of the content component as a DOM element;

determining, by a hashing module, a hash value for the DOM element using locality-sensitive hashing;

accessing, by a relevancy module, content component data that describes hash buckets and candidate content components assigned to the hash buckets using the locality-sensitive hashing, the candidate content components extracted from a corpus of HTML documents; and

generating, by a display module for display in a user interface, an indication of a particular candidate content component for inclusion in the HTML document based on a Manhattan distance between the hash value for the DOM element and a particular hash value determined for the particular candidate content component.

2. The method as described in claim 1 , further comprising adding, automatically and without user intervention, the particular candidate content component to the HTML document.

3. The method as described in claim 1 , further comprising generating a consistency score for the particular candidate content component that represents a number of features included in a DOM element representation of the particular candidate content component that are also included in the DOM element.

4. The method as described in claim 3 , wherein the features are weighted.

5. The method as described in claim 3 , wherein the features are not weighted.

6. The method as described in claim 1 , wherein the feature of the content component is at least one of style, context, or content.

7. The method as described in claim 1 , further comprising transferring a style of the particular candidate content component to an additional content component included in the HTML document.

8. The method as described in claim 7 , further comprising representing the particular candidate content component as a tree with nodes corresponding to features included in a DOM element representation of the particular candidate content component.

9. The method as described in claim 1 , wherein the locality-sensitive hashing is based on p-stable distributions.

10. The method as described in claim 1 , wherein the HTML document is an incomplete version of a template and the corpus of HTML documents includes a completed version of the template.

11. In a digital medium environment, a system comprising:

a document object model (DOM) module implemented at least partially in hardware of a computing device to:

extract a content component included in a hypertext markup language (HTML) document; and

represent a feature of the content component as a DOM element;

a hashing module implemented at least partially in the hardware of the computing device to determine a hash value for the DOM element using locality-sensitive hashing;

a relevancy module implemented at least partially in the hardware of the computing device to compute Manhattan distances between the hash value and hash values described by content component data, the hash values determined using the locality-sensitive hashing for DOM elements extracted from a corpus of HTML documents; and

a display module implemented at least partially in the hardware of the computing device to generate, for display in a user interface, indications of candidate content components for inclusion in the HTML document based on the Manhattan distances.

12. The system as described in claim 11 , wherein the indications of the candidate content components include consistency scores that represent a number of features included in the DOM element that are also included in DOM element representations of the candidate content components.

13. The system as described in claim 11 , wherein the indications of the candidate content components are generated as a list arranged in an ascending order of the Manhattan distances.

14. The system as described in claim 11 , wherein the indications of the candidate content components are generated as a list arranged in a descending order of the Manhattan distances.

15. The system as described in claim 11 , wherein the feature of the content component is at least one of style, context, or content.

16. A system comprising:

means for extracting a content component included in a hypertext markup language (HTML) document;

means for representing a feature of the content component as a document object model (DOM) element;

means for determining a hash value for the DOM element using locality-sensitive hashing;

means for accessing content component data that describes hash buckets and candidate content components assigned to the hash buckets using the locality-sensitive hashing; and

means for generating, for display in a user interface, an indication of a particular candidate content component for inclusion in the HTML document based on a Manhattan distance between the hash value for the DOM element and a particular hash value determined for the particular candidate content component.

17. The system as described in claim 16 , further comprising means for generating a consistency score for the particular candidate content component.

18. The system as described in claim 16 , further comprising means for transferring a style of the particular candidate content component to an additional content component included in the HTML document.

19. The system as described in claim 16 , further comprising means for adding, automatically and without user intervention, the particular candidate content component to the HTML document.

20. The system as described in claim 16 , wherein the feature of the content component is at least one of style, context, or content.