YOUR GO-TO INTELLIGENCE RESOURCE FOR THE SCHOLARLY PUBLISHING INDUSTRY

Knowledge graphs coupled with machine learning are becoming the go-to solution for enterprises looking to connect the data world and the business world. However, enterprises find it challenging to gain meaningful results from this potent combination. Therefore, KMWorld held a webinar to throw light on how to get started with knowledge graphs and machine learning and achieve Enterprise Artificial Intelligence (AI).

According to the experts, enterprises should use a simple iterative approach to achieve enterprise AI. The experts also explained the need for:

• Defining the overarching vision that outlines a clear meaning and business value of AI
• Selecting use cases that support future implementations such as natural language search, content and data governance and discovery, and compliance and operational risk prediction
• Using taxonomy, metadata, and data catalogs for classifying and categorizing both structured and unstructured information for findability
• Automating the process of inventorying millions of content items
• Laying the groundwork for getting information into a machine-readable format
• Using ontologies for mapping the relationships and connections existing between information and data components (both structured and unstructured)
• Increasing the discoverability of hidden content and information to optimize the search experience
• Laying the foundations for intelligent AI capabilities, like text mining and context-based recommendations

To sum up, enterprises should start small in a test environment to validate the data model iteratively against real data to show quick progress. Then follow it up by enhancing the knowledge graph by tagging internal and external sources of information. Next, develop a prioritized backlog to incrementally prove and deliver on Enterprise AI initiatives, like semantic search, optimized data management, and governance. Furthermore, iterate and scale with each new business question and data source.

Click here to read the original article published by KMWorld.