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Bibliographic Details
Main Authors: Kalamkar, Pratik N., Phakatkar, A. G.
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2510.23384
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author Kalamkar, Pratik N.
Phakatkar, A. G.
author_facet Kalamkar, Pratik N.
Phakatkar, A. G.
contents Opinions are central to almost all human activities and are key influencers of our behaviors. In current times due to growth of social networking website and increase in number of e-commerce site huge amount of opinions are now available on web. Given a set of evaluative statements that contain opinions (or sentiments) about an Entity, opinion mining aims to extract attributes and components of the object that have been commented on in each statement and to determine whether the comments are positive, negative or neutral. While lot of research recently has been done in field of opinion mining and some of it dealing with ranking of entities based on review or opinion set, classifying opinions into finer granularity level and then ranking entities has never been done before. In this paper method for opinion mining from statements at a deeper level of granularity is proposed. This is done by using fuzzy logic reasoning, after which entities are ranked as per this information.
format Preprint
id arxiv_https___arxiv_org_abs_2510_23384
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Opinion Mining Based Entity Ranking using Fuzzy Logic Algorithmic Approach
Kalamkar, Pratik N.
Phakatkar, A. G.
Artificial Intelligence
Machine Learning
Opinions are central to almost all human activities and are key influencers of our behaviors. In current times due to growth of social networking website and increase in number of e-commerce site huge amount of opinions are now available on web. Given a set of evaluative statements that contain opinions (or sentiments) about an Entity, opinion mining aims to extract attributes and components of the object that have been commented on in each statement and to determine whether the comments are positive, negative or neutral. While lot of research recently has been done in field of opinion mining and some of it dealing with ranking of entities based on review or opinion set, classifying opinions into finer granularity level and then ranking entities has never been done before. In this paper method for opinion mining from statements at a deeper level of granularity is proposed. This is done by using fuzzy logic reasoning, after which entities are ranked as per this information.
title Opinion Mining Based Entity Ranking using Fuzzy Logic Algorithmic Approach
topic Artificial Intelligence
Machine Learning
url https://arxiv.org/abs/2510.23384