What are the limitations of the semantic networks? A. Intractability B. Lack in expressing some of the properties C. Incomplete D. Has memory constraints

The correct answer is: All of the above.

Semantic networks are a type of knowledge representation that is used to represent the meaning of words and concepts. They are made up of nodes and links, where nodes represent concepts and links represent relationships between concepts.

Semantic networks have a number of limitations. One limitation is that they can be difficult to scale. As the number of nodes and links in a semantic network grows, it becomes more and more difficult to manage and update the network.

Another limitation of semantic networks is

Finally, semantic networks can be incomplete. They may not be able to represent all of the knowledge that is relevant to a particular domain.

Despite these limitations, semantic networks are a powerful tool for representing knowledge. They are used in a variety of applications, including natural language processing, information retrieval, and machine learning.

Here is a brief explanation of each option:

• Intractability: Semantic networks can be difficult to
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  scale. As the number of nodes and links in a semantic network grows, it becomes more and more difficult to manage and update the network.
• Lack in expressing some of the properties: Semantic networks can be difficult to understand. The meaning of a semantic network is not always clear, and it can be difficult to determine the relationships between concepts.
• Incomplete: Semantic networks can be incomplete. They may not be able to represent all of the knowledge that is relevant to a particular domain.