According to W3C (https://www.w3.org/WAI/ARIA/apg/example-index/breadcrumb/index.html) the output should be:
<nav aria-label="Breadcrumb" class="breadcrumb">
<ol>
<li>
<a href="../../">
WAI-ARIA Authoring Practices
</a>
</li>
<li>
<a href="/WAI/ARIA/apg/patterns/">
Design Patterns
</a>
</li>
<li>
<a href="/WAI/ARIA/apg/patterns/breadcrumb/">
Breadcrumb Pattern
</a>
</li>
<li>
<a href="index.html" aria-current="page">
Breadcrumb Example
</a>
</li>
</ol>
</nav>
]]>Do you plan to provide the means of implementing the events schema so that events appear as “rich results” in Google search results? Here is the structure data documentation they provide in this regard:
https://developers.google.com/search/docs/advanced/structured-data/event
I am trying to make my theme output valid with xhtml5, but the function rest_output_link_wp_head() generates invalid head tag including an URL as a rel value. <link rel=”https://api.w.org/” href=”%s” />
I can remove this with a function, but that would be plugin territory in case I want to upload my theme to www.remarpro.com.
Why is this necessary? Why is invalid? Is there a workaround? Can this change to be valid in the future?
Thank you.
]]>Thank you.
]]>H1, H2, and preformatted ones like Cover, List, Quotes, etc.
After a text element is placed on a page/scene, is there a way to know after the story is constructed all the elements (HTML) tags in the story?
If we are strict for SEO purposes, ideally there is only one H1, multiple H2’s, and H3’s
It would be nice to know, either before or after, the complete structure of the story.
Thouhgts?
Terry
]]>I’m looking for a solution to implement a solution of semantic analysis of the 3000+ articles on my wordpress.
The idea is to get a tool that would parse the posts in order to obtain a list of the most used words in general and by each author.
With the possibility to exclude non-important words from the search, such as articles, conjunctions & linking words, etc.
Do you know if such a solution (plugin?) already exists?
Thanks!
Mat
]]>This tool combined the easy tagging and suggesting, semantic tagging (which I didn’t came across), and the knowledge graph and vocabulary being build at the same time, with engaging and insightfull widgets, easy to embed.
After having a few discussions with Gennaro, one of the guys on the team, I thought it was wise to try out.
And against my expectations I saw search traffic increase by 30% compared to last month, even comparing a longer period to last year, I saw increases of 60% in search traffic.
It’s the unique combination of not just tagging, but preparing the terms for search engine to understand what the page is about, in combination with the ease of use.
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