Knowledge Acquisition: Definition & In-Depth Explanation

For any business to achieve great success, their main goal is to enhance the competitive advantage of implementing expert systems. But how to achieve it? Any organization or individual can grab the benefit of dealing with knowledge elicitation to capture, organize, and share knowledge using Knowledge Acquisition.

What is Acquired Knowledge?

Acquired knowledge is the one that organizations receive from external sources. External sources play a vital role in representing the full-scale view of the value chain for the organization.

What are these external sources then?

They are Customers, Suppliers, Competitors, and Partners/Alliances.

What are their primary roles in terms of the knowledge acquisition process?


What is Knowledge Acquisition? Knowledge Acquisition is the process that an organization tries to acquire from external sources. External sources play a vital role in representing the full-scale view of the value chain for the organization. The Knowledge Acquisition process smoothly included the activities and tasks of knowledge engineering to fill the books and quickly increase knowledge management (KM) strength to a great extent. It is entangled connected to the corporate strategy that helps an individual or team gain massive KM roles on a large scale. What are these external sources then? They are Customers, Suppliers, Competitors, and Partners/Alliances. What are their primary roles in terms of the knowledge acquisition process

These three forms of knowledge for customers apply to knowledge acquisition and also to data or information. Further, the processing of such data can quickly be processed and used for the knowledge creation process and principles.

Knowledge sharing is an essential metric as it comes up with various forms based on business size. Knowledge Management plays a significant role in performing B2B relationships that, on one side, include the buyers to purchase more products.

On the other hand, the products can quickly be customize as per the customer’s need to a great extent.

Do you know what KM can do concerning knowledge sharing and acquisition?

  • Feedback collection
  • Analysis of marketing-related details
  • Suggestion Collection
  • Designing/Development Involvement


what KM can do concerning knowledge acquisition

The knowledge acquisition in terms of data and information for suppliers can quickly be processed and can perform as knowledge creation building blocks.


It involves a simplistic approach by collecting, managing, and performing its data, information, and knowledge presentation. Such details make it relatively easy for the customers to search, retrieve, and analyze it.

Many such knowledge engineering approaches fall under the information management scope. Still, the main target is to opt for component usage with an appropriate decision-making ability to create new knowledge or transfer knowledge.



Proper and responsive management is mandated to identify valuable data resources as a potential benefit. One of the best recommendations is to deal with the two-way learning aspect: There is no specific end to the relationship, and your today’s partner can become your competitor tomorrow.


Looking For An Easier Knowledge Transfer Process?

CloudTutorial will make your knowledge transfer process easier than ever. Create SOPs, guides, and FAQs in clicks!

Characteristics of Knowledge Acquisition

The term “Knowledge Acquisition” helps the organization deal with the various thought processes between the employee and business on a large scale. However, there are essential characteristics that define knowledge acquisition:

  1. Strong List of Questionnaires

    With the combination of the various techniques, including conferences, it becomes quite possible to handle the list of questions that match the best as per the business requirements.

  2. Decision Trees Methodology

    For any knowledge engineer, the essential tools are the decision trees to deal with prototyping knowledge representations. In other words, they are of prime importance to knowledge acquisition, specifically on several different levels of artificial intelligence applications. The majority of the knowledge engineers came with the solution that experts show more interest in, usually relating to decision trees than rules.

  3. Impressive Rule Development

    The rules are the easiest way to utilize data characterizing during knowledge acquisition rather than opting to use complex representation methodologies. The most efficient pivotal point to redirect the knowledge acquisition course process is to apply the prototypic regulations on a large scale

    During the interview process, the extra cases help the rule base expand on a large scale to deal with rule development. As a result, it helps provide an efficient way of feedback to structure the employees’ interviews

Theoretical Considerations

Human experts primarily use reasoning or pattern-recognition capabilities in building Expert Systems based on their particular knowledge and specialized intelligence. The expert system must be curious and possess a completely different classification concerning algorithms and database functionalities.

  1. Domains

    To determine whether an expert system suits the best for a specific problem domain, various features of the domain relate to knowledge acquisition.

    • First, authentic experts, people possessing acknowledged expertise in the domain, must be available.
    • Second, a general agreement among expert professionals about the precision of solutions in a domain should be available.
    • Third, the knowledge engineer domain expert should quickly communicate with colleagues details of their problem-solving methods.
    • Fourth, there should be narrow domain concepts with well-maintained solutions within the business network that do not require sense.
  2. Experts

    There are often various sources like books, guide manuals, advertisements, and simulation models; expert professionals use well-developed expert systems to a great extent.

    The primary role of the expert professional when selecting a domain expert is not astonishing.

    • First, an agreement must exist between the expert and the project’s goals.
    • Second, better work cooperation for the expert and ease in working.
    • Third, a domian expert must have impressive and effective verbal communication skills.
    • Fourth, the expert’s commitment to the application to be on-time.
  3. Knowledge Acquisition Technique

    The interview is the heart of the process. The domain’s heuristic model extracts through a sequence of intense, well-ordered meetings that go through extension over many months.

    Remember that expert professionals and knowledge engineers are not the same people. It is because the more profound the experts’ knowledge, the less they can describe their logic.

    Moreover, the efforts to describe their process, expert professionals tend to justify their knowledge, leading to misleading factors.

    The knowledge management methods include the general suggestions as mentioned below:

    • Observation of an individual solving the obstacle
    • Identification of data and process kind for solving the problem types using discussions
    • Develop scenarios with the expert professional to associate with different project problem types or theories
    • They possess an individual’s skills to resolve verbal mode problems and follow the essential steps of rational components
    • Rules implementation to be defined for meetings and problem-solving capabilities on a large scale

      Using expert systems requires a close working relationship between the knowledge engineer and the expert.


Want to Help Your Employees Find Information Quickly?

CloudTutorial makes it easy to find specific articles using categories and sub-categories options.

Guidelines for Knowledge Acquisition Process

Five essential guidelines help the organization to deal with the knowledge acquisition process on a large scale.

Guidelines for Knowledge Acquisition
  1. Process the material semantically

    The optimization of knowledge acquisition is mandatory to manage knowledge semantically. It becomes relatively easy for individuals or learners seeking to opt for learning new material-based info.

    As per the research studies of Fergus Craik and Endel Tulving, the proof of importance for semantic processing came into existence. They came up with an idea where the participants can answer the questions correctly regarding the target words by merely following the depth of processing functionality.  Confused? Let us take a simple example to explain it more clearly.

    Consider the semantic question: Which of the following words fits the best as per the sentence: John met a _____ on the playground”? Friend or tree

    This question invokes a detailed depth of processing that phonemic questions. Now, what is this phonemic? Which following rhymes with “late”? Crate or Tree

    Moreover, the phonemic questions have greater depth than questions related to structure format. HOUSE or house – Which term is in capital letters?

    From the above example mentioned above, the term processing activities using the semantic method is much better than using phonemically or structurally.

  2. Process and Retrieve Information Frequently

    The next learning objective is to perform testing and information retrieval multiple times. Now this reclaiming info, also known in other words, self-producing classification, can quickly be compared with just analyzing or copying it.

    The research of the “generation effect” phenomenon or topic came into existence. It has taken decades to understand that the analyzing or copying approach takes less time or effort of memory than creating a new item or self-producing decision approach.

    As the info reclining takes place, learning improvements exist just like academic functions deal with constant afterward or quizzes. Performing breaks up or distributing fetching strives to be the topmost factor.

  3. Learning and Retrieval Conditions should be Similar

    Generally, the knowledge representation of the knowledge works as per the relevant situations and internal and external context of the learning process. The info is perfect only when studying and retrieval are working in a in similar behavior.

    For instance, consider the sentence: I like CHIP DIP. Here the participants include one adjective and one noun, and both are in capital letters. They are being informed that the noun memories will be performed afterward.

    During the phase of the recognition test, participants are provided with a noun using:

    • Original adjective: CHIP DIP
    • With different adjective: SKINNY DIP
    • Without adjective: DIP

    In addition to it, to test memory, the distinction of encoding is a vital part of any organization. Different questions tend to provide different understanding levels. The best examples recall data, typically dealing with varying levels of understanding, and unlike mental operations or theories, then information recognition tasks.

  4. Connect New Information to Prior Knowledge

    With the initiation of new material, knowledge retention exists that quickly links to proper and prior data that is interconnected to each other.

    With prior knowledge, the readers grab the advantages to fill contextual gaps that occur within the text. It eventually creates a better global understanding of the text.

    To gain successful comprehension of the given text, prior knowledge is a must to make an accurate understanding of the text to a great extent.

  5. Create Cognitive Procedures

    Retaining and accessing procedural knowledge is relatively easy. It includes the relevant methods or shortcuts to complete a specific task and developing new memory strategies to enhance the distinct topic.

    Usually, multiple mnemonic categories exist to increase the data recall strategy, but the most popular references are the “method of loci.” Its primary purpose is to retain a long speech to get rid of using pen and paper.


Knowledge Acquisition is the process that is bounded by the following essential set of sources:

  • Customers
  • Suppliers
  • Competitors
  • Partners/Alliance

Nowadays, in this technological world, there are enormous ways to deal with knowledge construction. Some of the best are:

  • Research Meticulously
  • Reading Books
  • Operate Consciously
  • Harness Productivity
  • Complete Believe in Yourself

The four methods of acquiring knowledge is divided into four categories. Each category has its own strengths and weakness:

  • Intuition
  • Reading Books
  • Authority
  • Rationalism and Empricism
  • The Scientific Method

I hope you got clear references from knowledge acquisition tools and terminologies to be applied to your organization.

For the successful development of expert systems within the organization, it becomes quite mandatory to recognize the central role of knowledge acquisition.

Once the specific domain is available, then the expert must keep in mind the best practices to enhance the business performance to a great extent.

Ready To Try Our Knowledge Base Software?
Go with CloudTutorial or waste 100’s of $$$ on clunky tools with features that you don’t even use