knowler generates a knowledge graph using as a model a set of ontologies to enhance searches and recommendations
It is natural to ask what is behind all those systems that we use daily and that make it easy for us to find exactly what we were looking for in the tidal wave of the information hosted on the Internet, or that allow us to arrive on time for our appointments thanks to their recommendations to move and even take care of our health with suggestions about physical exercise to practice during the day. To know the ins and outs of Artificial Intelligence, which has been established as a permanent trend even if it takes much longer than we suspect in our pockets and our devices, and is already integrated into all types of technological solution developed or to be developed, nothing better than take a look at the Gartner Hype Cycle for Emerging Technologies curve. To gauge that impact of Artificial Intelligence, we can check all the AI-related technologies that appear in the Hype Cycle, but we are going to keep those knowledge graphs that are linked to knowler.
A knowledge model is established trough the ontologies, “a formal and explicit specification of a shared conceptualization” (Thomas R. Gruber, 1993), that allows to express the semantics necessary to link different resources, generating this way what we call knowledge graph. It is a model that integrates different data schemas, serving as an “umbrella” to integrate information or to access it in a federated way. In addition, ontologies allow discovering new knowledge through inference rules. This is how knowler creates that knowledge base, using ontological models and inference rules, and relates it to its powerful search engine tool to find exactly what you need using even natural language.
However, in addition to integrating information through ontologies on RDF triplet repositories, property graphs are also used by transforming our knowledge graph into different specific views for different knowler functionalities, in addition to providing us with the ability to apply Artificial Intelligence algorithms over graphs. In this way, knowler brings out the full potential of ontological models and “property paths”, always being efficient, depending on the type of operation you want to perform on the data.
In summary, the background of knowler is a complex system that organizes and relates the information of a company, turning it into knowledge by putting all the power of the data available to everyone and adding value in the day-to-day life of the Company employees.
Information provided by Enrique Solano, Senior Lead Knowledge Engineer of knowler team, and Carlos Bobed, Phd. in Computer Science of knowler team.
