NLP interview questions

NLP interview questions | Freshers & Experienced

  • Pradeep
  • 11th Nov, 2019

Natural Language Processing (NLP) Interview Questions

Q1. What is NLP?

NLP stands for Natural Language Processing. This NLP can be defined as the manipulation of the natural language such as speech, text. This manipulation is automatic and is done by software. Studies for natural language processing or in short for NLP has been going on for over 50 years in a row now. And it is also now separated from the linguistics field due to the emergence of computers.

Q2. What are the applications of NLP?

There are various applications of Natural Language Processing (NLP) in the computer world. NLP uses artificial intelligence, computer science, and computational linguistics to allow the machines to read the text.

The applications of NLP are as under:

  • Summarization of information: NLP helps in understanding the meanings of the data. It helps you to identify important information and avoid irrelevant data.
  • Classification of the text: Through NLP, you can classify the information into various categories.
  • Knowing the sentiments of the customers: Many companies make use of NLP to identify the sentiments of the customers from their reviews and opinions.

Q3. How does NLP work?

Q4. List some areas of NLP?

Q5. What's NLP's role in social media?

Q6. What is morphology in NLP?

Morphology in NLP is defined as the study of the structure of words and how the words are formed. It identifies the root of the word and the prefix and suffix which are attached to the root of the word. For example, take a word "unhappiness", here if we see the formation of the word then we will come to know that prefix is "un", the root is "happy", a suffix is "ness". This study of word formation and identification of the structure of a word is known as Morphology.

Q7. Why is NLP hard?

Q8. What is the difference between NLP and NLU?

Q9. What is Stemming in NLP?

Stemming in NLP is the process of reducing a word of any sentence to its word stem or to the root of the word which is also known as a lemma. Stemming is very crucial in NLP (natural language processing) as well as in NLU (natural language understanding). By understanding the form of the word makes it possible to search for more related results that have been missed. This additional information is the result of the stemming process; that is why this process is considered very crucial in NLP. Stemming can be performed by an individual or an algorithm; once the root word is found, it explores new results related to that content.

Q10. What is FSA recognition?

A model out of many others for a computer that is abstract and does the following is known as Finite State Automaton:

  • Efficient reading of input strings
  • And modifies the internal state of that string as per the present input symbol.

The FSA can also accept or reject an input string. All the automation has a language which is the collection of strings that it would accept.

Q11. What are some open-source NLP libraries?

Q12. Why is NLP relevant?

Q13. What is pragmatic analysis in NLP?

Pragmatic analysis in NLP (Natural Language Processing) is then defined as the process of extracting information from any given text. There is various text whose meaning does not contradict with the reference in which they are written. In that case, there is a need to extract useful information from that text and Pragmatic analysis is a part of that information extracting process. It takes a structured set of any given text and finds out what the actual meaning was. It is a crucial process in which we obtain useful information and exact meaning which any particular text wants to convey.

Q14. List some Components of NLP?

There are five main components of NLP (Natural Language processing); these are

  • Morphological and lexical Analysis- This process finds out all the possible solutions for any given problem.
  • Syntactic Analysis- It is done to understand the grammar and co-relation which exists between the words of any particular sentence so that the computer may not be confused by the grammar rules.
  • Semantic Analysis- This is done after performing the syntactic analysis to understand the meaning of the word.
  • Discourse Integration- It makes sense of any context of a sentence.
  • Pragmatic Analysis- This is done to extract useful information from any sentence.

About Author :

  • Author of NLP interview questions

    Pradeep Kumar

    Pradeep Kumar is proficient python programmer with experience in different technologies like Python Django, Scrapy, Angular JS and others languages. He have also worked on customization of test automation using Katalon Studio based on Groovy Language.

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