Leveraging Fuzzy Logic for Accurate Compound Noun Extraction in Textual Data
Latifa Rassam, Imane Ettahiri, Ahmed Zellou, Karim Doumi · 2024
The extraction of compound nouns from textual documents poses a significant challenge due to the complex and variable nature of linguistic structures. Traditional approaches struggle to accurately capture the nuanced semantics of compound nouns because they rely strictly on exact matches. In this research, we emphasize the importance of using fuzzy logic to address the challenges stemming from ambiguity and imprecision in extracting compound nouns. By leveraging the flexibility of fuzzy logic, we propose a novel approach that exceeds the limitations of traditional methods. Our method embraces the adaptability of fuzzy logic and offers a powerful and context-aware solution for extracting compound nouns. Through empirical evaluation and comparison with traditional approaches, our fuzzy logic-based methodology demonstrates superior performance in capturing the diverse expressions of compound nouns. By incorporating fuzzy logic, our approach excels in handling the variations and uncertainties present in natural language, ultimately providing a more accurate and nuanced representation of compound nouns in textual documents. This research not only advances the field of compound noun extraction but also highlights the effectiveness of fuzzy logic in overcoming challenges associated with the intricacies of language in information extraction tasks.