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2.  ………………………. is a free, open-source library for Natural Language Processing (NLP) in Python.
                    3.  ………………………. is an open-source NLP library designed for topic modelling and document similarity analysis.
                    4.  A ………………………. can be any word or number or special character that forms a part of a sentence.
                    5.  The entire set of text from all the documents altogether is known as ………………………..
                    6.  Google Assistant, Alexa, Cortana, are best examples of ………………………..
                    7.  ………………………. and ………………………. are the types of chatbots.
                    8.  In ………………………. the selected text, phrases, sentences or sections are extracted from the scattered resources and
                       joined appropriately to form a concise summary.
                 C.  State whether these statements are true or false.

                    1.  Every computer language has its own syntax and semantics which needs to be followed strictly.   ……….……
                    2.  NLP has become a transformative force in modern technology.                               ……….……
                    3.  There are three different ways of creating Automatic text summarisation.                  ……….……

                    4.  Stemming is a slower process.                                                             ……….……
                    5.  BoW is considered better than TFIDF technique in NLP.                                     ……….……
                    6.  Communication through text and speech in humans is a difficult method.                    ……….……
                    7.  Business organisations gain insights on consumers using Automatic Text summarisation.     ……….……
                    8.  Virtual Assistants classifies the unstructured text into groups or categories.            ……….……


                                                  SECTION B (Subjective Type Questions)

                 A.  Short answer type questions.
                    1.  What is NLP?
                    2.  Define language translation.

                    3.  What do you mean by the term Script-bot?
                    4.  What is Automatic Text Summarisation?
                    5.  Name the techniques of Natural Language Processing.

                 B.  Long answer type questions.

                    1.  Differentiate between human languages and computer languages.
                    2.  Write any two applications of NLP.
                    3.  Explain sentiment and emotion analysis.
                    4.  Explain the term chatbots.

                    5.  Differentiate between stemming and lemmatization.
                    6.  Explain any two applications of TFIDF.

                                                                                                      #Critical Thinking
                 C.  Competency-based/Application-based questions.                            21 st  Century   #Information Literacy
                                                                                                  Skills
                    1.  Sonam is trying to understand the process of Lemmatization. Help her in filling up the following table by suggesting
                       appropriate affixes and stem of the words mentioned there:

                           S.No            Word                Affixes              Lemma

                            1       Tries
                            2      Learning


                                                                                  Natural Language Processing   259
   256   257   258   259   260   261   262   263   264   265   266