Convolutional Neural Network CNN: What Are the Key Knowledge Representation Techniques in AI and Their Applications?

Explore the main knowledge representation techniques in AI, including frames, conceptual dependencies, associative networks, and scripts, and understand their specific applications in artificial intelligence.

Question

Match the following knowledge representation techniques with their applications:

List – I List – II

(a) Frames (i) Pictorial representation of objects, their attributes and relationships

(b) Conceptual dependencies (ii) To describe real world stereotype events

(c) Associative networks (iii) Record like structures for grouping closely related knowledge

(d) Scripts (iv) Structures and primitives to represent sentences

code:

a b c d

A. (iii) (iv) (i) (ii)
B. (iii) (iv) (ii) (i)
C. (iv) (iii) (i) (ii)
D. (iv) (iii) (ii) (i)

Answer

A. (iii) (iv) (i) (ii)

Explanation

Let’s break down each knowledge representation technique and its corresponding application:

Frames (a) – (iii)

Frames are record-like structures used for grouping closely related knowledge. They consist of a collection of slots and slot values, which can be of various types and sizes. Frames are organized into hierarchies or networks, allowing for the inheritance of information from upper-level frames to lower-level frames1.

Conceptual Dependencies (b) – (iv)

Conceptual dependencies are structures and primitives used to represent sentences. This technique is based on a limited number of primitive concepts and formation rules to represent natural language statements. Conceptual dependency theory aims to capture the maximum concepts to provide a canonical form of meaning for sentences.

Associative Networks (c) – (i)

Associative networks, also known as semantic networks, are pictorial representations of objects, their attributes, and relationships. They consist of nodes representing objects and arcs describing the relationships between those objects. Semantic networks are easy to understand and can be easily extended.

Scripts (d) – (ii)

Scripts are used to describe real-world stereotype events. They are frame-like structures that represent commonly occurring experiences, such as going to a restaurant or visiting a doctor. Scripts provide a way to organize and represent knowledge about typical situations and sequences of events.

Key Differences and Applications

1. Frames are useful for representing structured knowledge about objects or concepts, making them ideal for object-oriented knowledge representation.
2. Conceptual dependencies are particularly effective for natural language processing and understanding, as they provide a way to represent the meaning of sentences in a standardized format.
3. Associative networks excel at representing relationships between concepts and are often used in knowledge graphs and ontologies.
4. Scripts are valuable for representing procedural knowledge and stereotypical sequences of events, making them useful in planning and reasoning about common situations.

By understanding these knowledge representation techniques and their applications, AI systems can effectively store, organize, and utilize knowledge for various tasks, including reasoning, problem-solving, and natural language understanding.

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