5 Key Steps: Integrate Knowledge Extraction with Popular Business Applications

Knowledge extraction automatically extracts structured information from unstructured or semi-structured data sources, such as text documents, websites, or databases. Knowledge extraction involves identifying and converting relevant pieces of information into a format that can be easily analyzed, organized, and stored. This process employs natural language processing (NLP), machine learning (ML), and data mining techniques to extract valuable insights, facts, or relationships from a large volume of data.

Knowledge extraction can be used in various applications, including information retrieval, text summarization, sentiment analysis, etc.

Another great thing for corporations wanting to use knowledge extraction for their information-finding is that they can integrate capable technologies into their existing applications and platforms – such as Salesforce, SharePoint, Office 365, chat applications like Microsoft Teams, and more.

Here are the 5 key steps businesses need to take.

1. Define Objectives

Clearly define your objectives for knowledge extraction. Understand what kind of information you want to extract and why.

• Do you need to give sales teams knowledge of customers?
• Do you need to provide product teams with market developments?
• Do you need to offer R&D teams with relevant information sources?
• Do you need to empower marketing teams with quick access to campaign statistics?

Or is it all the above and more?

Download Whitepaper: AI Guidelines for Businesses

2. Select the Knowledge Extraction Solution

Various natural language processing (NLP) and machine learning tools are available, such as Mindbreeze InSpire.

Which one is best for you? Likely, you will want to work with a solution that can do even more.

See the endless possibilities with Mindbreeze

3. Prepare the Data and Data Access

Ensure that the data in SharePoint, Salesforce, or other applications are clean, well-structured, and in a format that the chosen tools can easily process.

Set up access to your business platform data. Depending on the platform, you may need to use APIs or connectors.

Discover more on Mindbreeze’s Open Platform and API

4. Train the Model

Train or configure your knowledge extraction model. This may involve defining the entities, relationships, and attributes you want to extract from the data.

View our video and blog for more information on defining entities

5. Integrate and Test

Integrate the knowledge extraction model into your existing applications. This may involve custom development or using pre-built connectors or plugins provided by the knowledge extraction tools.

Test the integration thoroughly to ensure it accurately extracts the desired knowledge from your SharePoint and Salesforce data (or other preferred business tools).

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