and smart recommender systems
Use the power of a corporate knowledge graph to find what you need!
Your company has huge amounts of knowledge and hardly knows what it knows. Data and information are kept in siloes, corporate search functions are slow and provide poor results in a user-unfriendly format. Let´s have a look at Mr. Google? The search-function of Google is built on a huge – the world´s biggest – knowledge graph. This is a model of the global body of knowledge and any information that is on the web is linked with this model. Through a number of mechanisms google can identify you (e.g. from which part of the world you are searching) and can provide you the knowledge that you are looking for. However, Google doesn´t know your company and it doesn’t have access to your corporate data. An enterprise knowledge graph brings the full power of google-search into the companies and provides lot more of potential due to full access to data and user-profiles. It can provide smart recommendations, which lead users to knowledge they haven´t even been aware of, but which makes a difference for their work.
How we do it?
1. Strategy and design workshop
Knowledge.city facilitates workshops to strategize your way towards knowledge graph and Artificial Intelligence solutions. This helps to get a good understanding of the approach and how to create value for your company.
2. Starter kit
In a concentrated, efficient process of a few weeks, we will introduce the concept of knowledge graphs to the company and define use-cases for search and recommendation system that are practical, going into the details of operational processes and creating a tangible, working output.
• The starter kit will help understanding how to create value from semantic technologies, knowledge graphs and artificial intelligence solutions, taking up to 28 hours of web-based and f2f-training.
• A prototype of the knowledge graph will be developed and the validity of it will be tested, using real content by real people in real context.
• A pilot version of the semantic web tool will be implemented to manage the knowledge graph and develop the recommender system.
3. Full roll-out and maintenance
After successful prototyping the graph will be further developed and rolled out to all users. Additional use-cases can be developed towards a fully implemented KM- and AI-Strategy.
Results and benefits
- Find all company data as easy and fast as in google: Without data migration the knowledge graph analyses and enriches your content with metadata and links content with user profiles.
- Find more than you can look for: Recommender systems provide you access to the knowledge you need, but haven´t been aware of.
- Performance, cost, happiness: When easily finding the right knowledge, processes will run faster, quality of work will increase, and people enjoy the feeling of being fully informed and competent in decision making.