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Discussion Forum

Que. Slots and facets are used in
a. Semantic Networks
b. Frames
c. Rules
d. All of these
Answer:Frames
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Similar Questions:

Consider the following statements :

(a) Assignment problem can be used to minimize the cost.
(b) Assignment problem is a special case of transportation problem.
(c) Assignment problem requires that only one activity be assigned to each resource.

Which of the following options is correct?
Consider the following statements:

(a) If primal (dual) problem has a finite optimal solution, then its dual (primal) problem has a finite optimal solution.
(b) If primal (dual) problem has an unbounded optimum solution, then its dual (primal) has no feasible solution at all.
(c) Both primal and dual problems may be infeasible.
Which of the following is correct?
Which of the following can be used for clustering of data ?
Which of the following neural networks uses supervised learning?

(A) Multilayer perceptron
(B) Self organizing feature map
(C) Hopfield network
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
An artificial neuron receives n inputs x1, x2, x3............xn with  weights w1, w2, ..........wn attached to the input links. The weighted sum_________________ is computed to be passed on to a non-linear filter  Φ called activation function to release the output.
Slots and facets are used in
Identify the following activation function :
φ(V) = Z + (1/ 1 + exp (– x * V + Y) ),
Z, X, Y are parameters 
A neuron with 3 inputs has the weight vector [0.2 -0.1 0.1]^T and a bias θ = 0. If the input vector is X = [0.2 0.4 0.2]^T then the total input to the neuron is:
In propositional logic P ⇔ Q is equivalent to (Where ~ denotes NOT):
Match the following :

(i) OLAP                        (a) Regression
(ii) OLTP                        (b) Data Warehouse
(iii) Decision Tree        (c) RDBMS
(iv) Neural Network     (d) Classification

code:
      (i)   (ii)  (iii)   (iv)
In Delta Rule for error minimization
Back propagation is a learning technique that adjusts weights in the neural network by propagating weight changes.

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