Advanced Database Management System - Tutorials and Notes: Natural Language Processing (NLP) Multiple Choice Questions with answers

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Friday, 25 September 2020

Natural Language Processing (NLP) Multiple Choice Questions with answers

Top 5 MCQ on NLP, NLP quiz questions with answers, NLP MCQ questions, Solved questions in natural language processing, NLP practitioner exam questions


Multiple Choice Questions in NLP 

1. Zipf's law tells us:

(a) head words take major portion in English vocabulary;

(b) in a given corpus, if the most frequent word's frequency is 1, then the second frequent word's frequency is around 0.5;

(c) comparing to tail words, removing head words helps more to reduce the storage of documents represented by a vector space model when using a dense matrix data structure;

(d) smoothing is not necessary.

Answer: (b) in a given corpus, if the most frequent word's frequency is 1, then the second frequent word's frequency is around 0.5

Zipf’s law:

Zipf's law states that given a large sample of words used, the frequency of any word is inversely proportional to its rank in the frequency table. So a word that appears at position number n has a frequency proportional to 1/n.

The law examines the frequency of words in natural language and how the most common word occurs twice as often as the second most frequent word, three times as often as the subsequent word and so on until the least frequent word.

 

2. Which of the following is NOT a good example of cohesive device?

(a) Discourse markers

(b) Pronouns

(c) Prepositions

(d) Demonstratives

Answer: (c) Prepositions

Cohesive devices, sometimes called linking words, linkers, connectors, discourse markers or transitional words.

Cohesive Devices are words or phrases that show the relationship between paragraphs or sections of a text or speech. Cohesive devices are words like ‘For example‘, ‘In conclusion‘, ‘however‘ and ‘moreover‘. [For more, refer here]

 

3. In the sentence, “I want a cute teddy for my birthday”, the underlined part is an example of _____.

(a) Gerund phrase

(b) Verb phrase

(c) Prepositional phrase

(d) Adverbial phrase

Answer: None of these options are correct

The underlined text is a noun phrase.

A noun phrase is a word or group of words containing a noun and functioning in a sentence as subject, object, or prepositional object. It is a phrase that has a noun as its head or performs the same grammatical function as a noun.

In a simple definition, noun phrase is a group of words that function like a noun. Noun phrases are nouns with modifiers.

 

4. Which of the following is an advantage of GLoVE?

(a) The data can be fed into the model in an online way and needs little preprocessing, thus requires little memory.

(b) The model is trained on the co-occurrence matrix of words, which takes a lot of memory for storage.

(c) The model can quickly give different sized vectors via matrix factorization

(d) It prevents meaningless stop words like “the”, “an”.

Answer: both (c) and (d)

(c) Since the co-occurrence matrix is pre-computed GLoVE can quickly give different sized vectors via matrix factorization for which many efficient implementations are available.

(d) It gives lower weight for highly frequent word pairs so as to prevent the meaningless stop words like “the”, “an” will not dominate the training progress.

 

5. How to use WordNet to measure semantic relatedness between words:

(a) Measure the shortest path between two words on WordNet

(b) Count the number of shared parent nodes

(c) Measure the difference between their depths in WordNet

(d) Measure the difference between the size of child nodes they have.

Answer: (a) Measure the shortest path between two words on WordNet

WordNet is a lexical database of semantic relations between words.

Measuring the shortest path (ie., minimal number of edges) between two words in WordNet. The path length measure, Leacock-Chodorow, and Hirst & St-Onge are the similarity measures based on the shortest path concept. [A possible reference] 

 

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