The document discusses using artificial intelligence and big data in knowledge management. It covers extracting knowledge from data through information architecture and data curation. It then discusses utilizing AI to deliver knowledge through chatbots using natural language processing, predicting trending knowledge areas, and personalizing knowledge delivery. The goal is to provide knowledge management that is dynamic, accurate, and personalized through leveraging AI technologies.
Put into practice, Information Architecture (IA) connects people to content (Information & Knowledge) by incorporating:
Classifications and Hierarchies
Labels and Indexing
To improve Navigation and Search
Interacting with stored knowledge in repositories and connecting this explicit knowledge to the tacit knowledge holders brings together a holistic view of knowledge.
Tacit knowledge holders include the knowledge workers who are experienced with executing certain tasks, developing a solution, working in a specific industry, practice area or company while leveraging the stored knowledge.
Deep learning algorithms run data through several “layers” of the algorithm, each layer passes a simplified representation of the data to the next layer. This allows the algorithm to learn more as it passes through each layer. The ability to process large numbers of features makes deep learning very powerful when dealing with unstructured data.