Page 397 - AI Ver 3.0 class 10_Flipbook
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a. Both A and R are correct and R is the correct explanation of A.
b. Both A and R are correct but R is NOT the correct explanation of A.
c. A is correct but R is incorrect.
d. A is incorrect but R is correct.
3. Assertion (A): The lexicon of a language includes not only words but also their meanings.
Reasoning (R): Lexicon is the complete set of words used in a language, including definitions, forms, and meanings.
4. Assertion (A): Sentiment analysis is valuable for assessing market shifts, such as trends in fashion or customer
preferences.
Reasoning (R): By analysing public sentiment over time, sentiment analysis can provide businesses with valuable
insights into market trends and emerging consumer preferences.
In Life 21 st Century #Communication
#Social Interaction
Skills
Chatbots have come far over the years. Think of the benefits the we have received due to this wonderful invention.
Share your thoughts with the class.
Deep Thinking
21 st Century
Skills #Critical Thinking
Most of the apps that we use daily ask for our permission and ensure that our data is safe. They also ensure that
they are not keeping tabs on us. But, there are scenarios when we discuss something with our friends and the
same object appears in our ads. This happens even even if we have not looked up for that product. So, how is this
happening? Share your thoughts with the class.
21 st Century #Technology Literacy
Skills
Lab
1. Create a PowerPoint presentation to explain the various applications of NLP. Make separate slides for
each application and use graphics to make them attractive.
2. Find some more chatbots from the internet and write your information in a MS word file using their logos
as well as working of each chatbot.
Answers
Exercise (Section A)
A. 1. b 2. c 3. c 4. b 5. b 6. b 7. a 8. b
B. 1. NLP 2. Voice assistants 3. keyword extraction 4. words and phrases
5. Conversational agent 6. Google Translate 7. captions 8. 0 and 1
C. 1. True 2. False 3. False 4. False 5. True 6. False 7. False 8. False
Natural Language Processing (Theory) 395

