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Title:
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A MECHANISM TO ENHANCE PROPOSAL MERGING IN AN E-DELIBERATION SYSTEM |
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Author(s):
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Georgia Rokkou and Vassilis Triantafyllou |
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ISBN:
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978-989-8704-62 |
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Editors:
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Paula Miranda and Pedro Isaías |
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Year:
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2024 |
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Edition:
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Single |
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Keywords:
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Proposal Merging, E-Deliberation, Automated Data Processing, Natural Language Processing (NLP), Machine Learning
Algorithms |
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Type:
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Full |
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First Page:
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293 |
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Last Page:
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300 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This paper introduces an innovative method for automating the proposal merging process in e-deliberation systems,
utilizing advanced natural language processing (NLP) and machine learning algorithms. The primary goal is to efficiently
manage and consolidate lexically and conceptually similar proposals, thereby minimizing human intervention. Our
approach not only enhances the precision of proposal merging but also significantly reduces the time required for this task.
By automating this process, we improve the overall quality of proposals and streamline the deliberation process, resulting
in more organized and representative outcomes. Our findings demonstrate the potential of this methodology to advance
e-deliberation practices by ensuring a more accurate and efficient handling of public proposals |
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