Publications

Knowledge Representation: A Semantic Network Approach

Abstract: Knowledge representation is an emerging field of research in Artificial Intelligence, Big Data analytics, Semantic Web, and Data Mining. Effective knowledge representation facilitates easy traversal, searching, reasoning, prediction, and inference. Various approaches, algorithms, techniques, and models have been proposed, each with its own advantages and limitations. Our aim is to propose a simple yet highly effective method for representing knowledge, which offers greater expressiveness compared to logic and resonates with human cognitive processes. This paper discusses the implementation of a semantic network using a straightforward yet powerful method that yields accurate results despite the inherent vagueness of the English language. We detail the patterns discovered in sentences and the use of Natural Language Toolkit and Part-of-Speech tagging to simplify the task of tagging words with their respective parts of speech.

Link to Paper: Read the full paper

Keywords: Knowledge Representation, Semantic Network, Natural Language Processing, AI, Big Data, Semantic Web, Data Mining

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Feel free to explore the detailed research and findings in my publication. This work aims to enhance the field of knowledge representation by proposing a method that balances simplicity and effectiveness, ultimately improving the accuracy and usability of semantic networks.