Leveraging Linguistics and CS Class 11 NCERT Solutions

Leveraging Linguistics and CS Class 11 NCERT Solutions – The CBSE has updated the syllabus for St. XI (Code 843). The NCERT Solutions are made based on the updated CBSE textbook. All the important information is taken from the Artificial Intelligence Class XI Textbook Based on the CBSE Board Pattern.

Leveraging Linguistics and CS Class 11 NCERT Solutions

A.Multiple Choice Questions:

1. Which of the following is NOT a common task in NLP?
a) Machine translation
b) Text summarization
c) Speech recognition
d) Image recognition

2. What is the main challenge/s of NLP?
a) Handling Ambiguity of Sentences
b) Handling Tokenization
c) Handling POS-Tagging
d) All of the mentioned

3. What is a chatbot?
a) A physical robot used for chatting purposes.
b) A computer program designed to simulate conversation with human users, especially over the internet.
c) An advanced form of search engine.
d) A tool used for sending automated emails.

4. Which of the following is an application of Natural Language Processing (NLP)?
a. Autonomous vehicles
b. Predicting stock prices
c. Sentiment analysis
d. Virtual reality gaming

5. Which of the following statements about Voice Recognition Interfaces is true?
a. They solely rely on text-based inputs.
b. They are incapable of understanding multiple languages.
c. They convert spoken language into text or commands.
d. They require a physical keyboard for interaction.

B. Short answer questions:

1. How does NLP help in email filtering? Give a real-life example.

Answer: NLP is used in email filtering, NLP helps to identify patterns and keyword wheter email is spam or not. Once the NLP identify the emil is spam or not then email service automatically sort and filter the emails based on the content.

2. List the steps of NLP Processing.

Answer: Natural language processing (NLP) involves a series of five phases that enable machines to analyse, categorize, and understand both spoken and written language.

1. Lexical analysis
2. Syntactical Analysis
3. Semantic Analysis
4. Discourse Integration
5. Pragmatic Analysis

3. Briefly explain the two types of chatbots.

Answer: There are two different types of chatbots.

1. Rule-based chatbot: Operate on predefined rules and decision trees. Follow programmed rules to respond to user input. Easy to develop and maintain. Provide consistent and accurate answers to specific questions.
2. AI-powered chatbot: Utilise natural language processing (NLP) and machine learning algorithms. Also known as chat agents or virtual assistants. 24/7 availability for immediate and consistent support. Offer personalized interactions based on user preferences and history. Improve efficiency and cost savings by automating tasks and reducing service costs.

4. Briefly explain the classification problem. Give at least two examples.

Answer: Human language is full of terms that are vague or have double meanings. This is called a classification problem. in everyday language, phrases like “shipping a box by train” or “filling in a form by filling it out” may seem contradictory or confusing due to the double meanings of the words used.

5. Define the following:
(a) Intent (b)Entity (c) Dialog

Answer:

1. Intent: Intent An intent is a purpose: the reason why a user is contacting the chatbot.
2. Entity: An entity is a noun: a person, place, or thing. Once you have a list of the intents you want your chatbot to fulfil, you are ready to continue. If a user asks, “What are the hours for the Bangalore office?” then providing business hours is the intent, and Bangalore is the entity.
3. Dialogue: A dialogue is a flowchart—an IF/THEN tree structure that illustrates how a machine will respond to user intents. A dialogue is what the machine replies after a human asks a question.

C. Long Answer Questions:

1. Explain the structure of a chatbot.

Answer: A chatbot has a “frontend” and a “backend”.

• Frontend: The user can intract with the help of frontend which serves as the messaging channel and providing a user-friendly interface.
• Backend: The backend of chatbot is use for storing information, the chatbot backend is a place where the hard work takes place. The backend operates application logic and has enough memory to remember earlier parts of a conversation as dialog continues.

2. “A syntax tree is created as part of the procedure to visually represent semantic links.” Identify the phase of NLP processing?

Answer: The NLP processing first breaks down the words into pieces, and then NLP checks the pieces and how they connect to each other. After this, each word is arranged in a tree structure where each word is known as a node, and check the grammatical relationships between the pieces.

D. Case Study questions:

1. Imagine you are a customer service manager at a global e-commerce company facing increasing customer inquiries across multiple channels. To alleviate the strain on your support team and enhance customer satisfaction, you decide to implement a chatbot solution. Develop a case study outlining the challenges you faced, the criteria you used to select a chatbot platform.

Answer:

Background:

In an e-commerce company facing challenges regarding enquiries across multiple channels, the company wants to make one customer service chatbot for customer satisfaction and for the support team.

Challenges:

1. The biggest challenge is that the team has to handle a lot of enquiries at the same time.
2. Customers are trying to connect to the support team from email, SMS, voice call, etc., which makes it difficult for the support team to track everyone.
3. Due to heavyy traffic,, the company needss more staff to manage.

Solution:

The company can use a chatbot to help with the customer satisfaction.

1. The chatbot has to work well with the current system.
2. The chatbot should give answers in all the different ways based on the customer requirement.
3. The chatbot should understand the question correctly and reply accurately.

Implementation:

As per the challenges given above, we have to train the chatbot, and proper testing will be applied.

Result:

1. Chatbot can answer common questions immediately.
2. The support team will focus on only complicated issues.
3. Cost savings will be there.
4. Better customer satisfaction.

2. Imagine you are a customer experience lead at a telecommunications company, currently relying on a rule-based chatbot to handle customer queries. However, due to limitations in scalability and adaptability, you are considering a transition to an AIbased chatbot solution. Detail the challenges faced during the transition, and the observed impact on customer service efficiency and satisfaction.

Answer:

Background:

The telecom company is not able to handle the customer query properly due to a rule-based chatbot, so the company should switch to an AI-based chatbot.

Challenges:

1. The rule-based chatbot could not handle more queries.
2. The rule-based chatbot is not able to handle complex questions.
3. The rule-based chatbot has limitations.
4. The new AI chatbot can integrate smoothly with the existing chatbot.

Solution:

The new chatbot can implement an AI-based chatbot with better language understanding.

1. We collect a lot of past customer questions to train the AI.
2. We can set up a feedback option to keep improving the chatbot.
3. We selected an AI chatbot with better understanding and integration features.

Impact:

1. The new chatbot can handle more queries easily.
2. The new chatbot can understand complex questions.
3. The customer will be happy due to better responses.

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