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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM25199
Volume:
7 |
8 |
Aug 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This process involves using Natural Language Processing (NLP) techniques, specifically LSTM (Long Short-Term Memory) algorithms, to generate questions from text while ensuring semantic accuracy and syntactic coherence. Unlike tasks such as summarization and paraphrasing, generating questions requires not only understanding the text but also being able to frame questions that elicit specific information, thus necessitating answers. To overcome this challenge, the approach involves several steps. First, the text undergoes preprocessing with NLP techniques to remove irrelevant or redundant information, as well as to identify and extract
KEYWORDS
Publication Date
6/3/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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