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LLM extracts data from reviews to build fuzzy cognitive maps

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a method for constructing data-driven fuzzy cognitive maps (FCMs) using local large language models. The study demonstrates how a model like Qwen2.5-32B can extract quantitative data from text, which is then used to train an FCM. This approach was tested using hotel reviews from TripAdvisor, with a specific focus on Greek reviews to form a star topology FCM indicating reviewer preferences. AI

IMPACT This research demonstrates a novel method for leveraging local LLMs to extract structured data for complex modeling tasks like fuzzy cognitive maps.

RANK_REASON The cluster contains an academic paper detailing a novel application of LLMs in constructing fuzzy cognitive maps.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LLM extracts data from reviews to build fuzzy cognitive maps

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The cluster contains an academic paper detailing a novel application of LLMs in constructing fuzzy cognitive maps.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Alexis Kafantaris ·

    LLM for the development of FCM

    arXiv:2607.04983v1 Announce Type: cross Abstract: This article is about the development of a fuzzy cognitive map using a local large language model. In the light of recent advances it is evident that large language models, and even local large language models are capable of extra…

  2. arXiv cs.AI TIER_1 English(EN) · Alexis Kafantaris ·

    LLM for the development of FCM

    This article is about the development of a fuzzy cognitive map using a local large language model. In the light of recent advances it is evident that large language models, and even local large language models are capable of extracting quantities from textual data. In other words…

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