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Policy Split: Incentivizing Dual-Mode Exploration in LLM Reinforcement with Dual-Mode Entropy Regularization METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning Do LLMs Know Tool Irrelevance? 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Opinion Mining Based Entity Ranking using Fuzzy Logic Algorithmic Approach
Pratik N. Kalamkar, A. G. Phakatkar · 2025-10-27 · via cs.AI updates on arXiv.org

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.

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