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Unit V question bank by PS Dolare
Ques bank
Course
BE IT (2019) (414442)
234 Documents
Students shared 234 documents in this course
University
Savitribai Phule Pune University
Academic year: 2022/2023
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Unit V
(NLP Questions each for 10 marks)
Document Processing and Text Mining
Prajakta Dolare (Asst. Prof.)
DVVP,COE Ahmednagar
- Explain text summarization & multiple document text summarizations with neat diagram.
- Describe different ways of building belief models in a conversational agent.
- Explain the process of multi-document summarization.
- What is automatic document separation, and how does it work?
- What are some of the advantages of using probabilistic classification and finite-state sequence for automatic document separation?
- How can automatic document separation be applied in real-world settings, such as in the legal or healthcare industries?
- What challenges might arise when using automatic document separation and how can these challenges be addressed?
- How does automatic document separation fit into the larger field of text mining, and what are some potential applications for this technology?
- What are some common challenges in data preparation for document processing or text mining?
- What are some techniques for cleaning and preprocessing data?
- How can you evaluate the quality of your data after preprocessing?
- How does the quality of data affect the outcome of a modeling task?
- How can you formulate document separation as a sequence mapping problem?
- What are some algorithms or models used for document separation?
- Can you provide an example of a document separation task and how it was solved?
- What are some evaluation metrics used to measure the performance of document separation models?
Was this document helpful?
Unit V question bank by PS Dolare
Course: BE IT (2019) (414442)
234 Documents
Students shared 234 documents in this course
University: Savitribai Phule Pune University
Was this document helpful?
Unit V
(NLP Questions each for 10 marks)
Document Processing and Text Mining
Prajakta Dolare (Asst. Prof.)
DVVP,COE Ahmednagar
1. Explain text summarization & multiple document text summarizations with neat diagram.
2. Describe different ways of building belief models in a conversational agent.
3. Explain the process of multi-document summarization.
4. What is automatic document separation, and how does it work?
5. What are some of the advantages of using probabilistic classification and finite-state sequence for
automatic document separation?
6. How can automatic document separation be applied in real-world settings, such as in the legal or
healthcare industries?
7. What challenges might arise when using automatic document separation and how can these
challenges be addressed?
8. How does automatic document separation fit into the larger field of text mining, and what are
some potential applications for this technology?
9. What are some common challenges in data preparation for document processing or text mining?
10. What are some techniques for cleaning and preprocessing data?
11. How can you evaluate the quality of your data after preprocessing?
12. How does the quality of data affect the outcome of a modeling task?
13. How can you formulate document separation as a sequence mapping problem?
14. What are some algorithms or models used for document separation?
15. Can you provide an example of a document separation task and how it was solved?
16. What are some evaluation metrics used to measure the performance of document separation
models?
