Building a Knowledge Base is usually hard work for the company, and developers are always scared of writing documents. I found an effective way to do this based on artificial intelligence methods.
This report explores a data-driven approach to knowledge base (KB) construction utilizing artificial intelligence (AI) methods. It highlights the challenges of traditional KB development and proposes a solution that leverages data mining and natural language processing (NLP) techniques.
Data mining and human experience
In normal cases, we need a technical developer and expert client management to understand the system and application’s requirements. Also, it is necessary to focus on writing documents instead of focusing on business. Most of the time, it is not possible for them to build a knowledge-based document.
However, data mining refers to new opportunities to better understand clients’ requirements and application problems. In this method, data scientists extract the data from clients’ questions and analyze their requests to discover company problems.
How do Data scientists make a knowledge base document?
When clients ask questions or send a request in CRM, they seek answers to their problems. Believe it or not, when a group of clients ask the same question or have the same problem, it shows us a problem inside our application. Furthermore, in many cases, they ask their question in the same words. Client literature may be different from the literature of developers and business owners. Data scientists can cluster these same questions into one big group and find similar questions or requirements. Then investigate the application for these big groups. These big groups showed us the problem inside our application.
On the other hand, in CRM, agents answer customers and similar instructions can be found in their answers. The clustering of these answers shows us how to build a knowledge base document for our company.
A large language model can be extremely helpful in these cases for finding topics and category instructions and even making FAQ questions.
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