Extract Structured Content, Tag Concepts & Entities
Cognonto is brand new. At its core, it uses a structure of nearly 40 000 concepts. It has about 138,000 links to external classes and concepts that defines huge public datasets such as Wikipedia, DBpedia and USPTO. Cognonto is not a children’s toy. It is huge and complexâ€¦ but it is very usable. Before digging into the structure itself, before starting to write about all the use cases that Cognonto can support, I will first cover all of the tools that currently exist to help you understand Cognonto and its conceptual structure and linkages (called KBpedia).
The embodiment of Cognonto that people can see are the tools we created and that we made available on the cognonto.com web site. Their goal is to show the structure at work, what ties where, how the conceptual structure and its links to external schemas and datasets help discover new facts, how it can drive other services, etc.
This initial blog post will discuss the demo section of the web site. What we call the Cognonto demo is a web page crawler that analyzes web pages to tag concepts, to tag named entities, to extract structured data, to detect language, to identity topics, and so forth. The demo uses the KBpedia structure and its linkages to Wikipedia, Wikidata, Freebase and USPTO to tag content that appears in the analyzed web pages. But there is one thing to keep in mind: the purpose of Cognonto is to link public or private datasets to the structure to expand its knowledge and make these tools (like the demo) even more powerful. This means that a private organization could use Cognonto, add their own datasets and link their own schemas, to improve their own version of Cognonto or to tailor it for their own purpose.
Let’s see what the demo looks like, what is the information it extracts and analyzes from any web page, and how it ties into the KBpedia structure.