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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM19743

EFFECTIVE SEARCH MECHANISM FOR SUGGESTIVE RESPONSE TO PARLIAMENT QUESTIONS (UTTAR)

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM19743

Volume:

7 |

4 |

Apr 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

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.

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Authors

TM

Tejas Mandora

PP

Premsagar Pawar

SP

Sanket Patil

KR

Ketan Rathod

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Abstract

Effective Search Mechanism for Suggestive Response to Parliament Questions is one of the reliable software mechanism to answer the member of parliament’s questions. During parliament session, each Department receives number of Parliament Questions (PQ) on varied topics raised by MPs. These PQ are to be handled in a very time bound manner on top priority. Each reply is generally prepared by seeking inputs from all the other relevant departments which requires lot of efforts and is also time consuming. It is desired a platform can be designed which can provide responses to similar PQ asked earlier, suggest probable reply and indicate different departments having similar programs and information. This will be helpful in preparing proper reply to PQ. Uttar is an A.I. based NLP model which helps to effectively search questions from the archive and provide approximate correct response. It is one of the most robust and effective mechanism for the parliament, because it will reduce time taken by officials to search through archive’s and question answer hours will become more productive with reduction in backlogs..

KEYWORDS

searching mechanism Parliament Questions approximate productive

Cite This Article

Tejas Mandora, Premsagar Pawar, Sanket Patil, Ketan Rathod, "EFFECTIVE SEARCH MECHANISM FOR SUGGESTIVE RESPONSE TO PARLIAMENT QUESTIONS (UTTAR)," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 4, Apr 2023.

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Publication Date

2/4/2023

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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