Information Retrival Techniques Set 6 MCQs

Q1 | In nearest neighbour case, the stored pattern closest to input pattern is recalled, where does it occurs?

feedback pattern classification

feedforward pattern classification

can be feedback or feedforward

none of the mentioned

Q2 | What is the field of Natural Language Processing (NLP)?

computer science

artificial intelligence

linguistics

all of the mentioned

Q3 | What is the main challenge/s of NLP?

handling ambiguity of sentences

handling tokenization

handling pos-tagging

all of the mentioned

Q4 | Choose form the following areas where NLP can be useful.

automatic text summarization

automatic question-answering systems

information retrieval

all of the mentioned

Q5 | Which of the following includes major tasks of NLP?

automatic summarization

discourse analysis

machine translation

all of the mentioned

Q6 | What is Coreference Resolution?

anaphora resolution

given a sentence or larger chunk of text, determine which words (“mentions”) refer to the same objects (“entities”)

all of the mentioned

none of the mentioned

Q7 | What is Machine Translation?

converts one human language to another

converts human language to machine language

converts any human language to english

converts machine language to human language

Q8 | What is Morphological Segmentation?

does discourse analysis

separate words into individual morphemes and identify the class of the morphemes

is an extension of propositional logic

none of the mentioned

Q9 | Which of the following clustering type has characteristic shown in the below figure?

partitional

hierarchical

naive bayes

none of the mentioned

Q10 | Point out the correct statement.

the choice of an appropriate metric will influence the shape of the clusters

hierarchical clustering is also called hca

in general, the merges and splits are determined in a greedy manner

all of the mentioned

Q11 | Which of the following is finally produced by Hierarchical Clustering?

final estimate of cluster centroids

tree showing how close things are to each other

assignment of each point to clusters

all of the mentioned

Q12 | Which of the following is required by K- means clustering?

defined distance metric

number of clusters

initial guess as to cluster centroids

all of the mentioned

Q13 | Point out the wrong statement.

k-means clustering is a method of vector quantization

k-means clustering aims to partition n observations into k clusters

k-nearest neighbor is same as k-means

none of the mentioned

Q14 | Which of the following combination is incorrect?

continuous – euclidean distance

continuous – correlation similarity

binary – manhattan distance

none of the mentioned

Q15 | Which of the following function is used for k-means clustering?

k-means

k-mean

heatmap

none of the mentioned

Q16 | Which of the following clustering requires merging approach?

partitional

hierarchical

naive bayes

none of the mentioned

Q17 | What is Machine learning?

the autonomous acquisition of knowledge through the use of computer programs

the autonomous acquisition of knowledge through the use of manual programs

the selective acquisition of knowledge through the use of computer programs

the selective acquisition of knowledge through the use of manual programs

Q18 | Which of the factors affect the performance of learner system does not include?

representation scheme used

training scenario

type of feedback

good data structures

Q19 | Different learning methods does not include?

memorization

analogy

deduction

introduction

Q20 | In language understanding, the levels of knowledge that does not include?

phonological

syntactic

empirical

logical

Q21 | A model of language consists of the categories which does not include?

language units

role structure of units

system constraints

structural units

Q22 | What is a top-down parser?

begins by hypothesizing a sentence (the symbol s) and successively predicting lower level constituents until individual preterminal symbols are written

begins by hypothesizing a sentence (the symbol s) and successively predicting upper level constituents until individual preterminal symbols are written

begins by hypothesizing lower level constituents and successively predicting a sentence (the symbol s)

begins by hypothesizing upper level constituents and successively predicting a sentence (the symbol s)

Q23 | Among the following which is not a horn clause?

p

Øp v q

p → q

p → Øq

Q24 | The action ‘STACK(A, B)’ of a robot arm specify to

place block b on block a

place blocks a, b on the table in that order

place blocks b, a on the table in that order

place block a on block b

Q25 | A is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility.

decision tree

graphs

trees

neural networks