Design and Evaluation of Electronic Business Ontology Based on Persian Language Processing

Ahmadi, Hamid

doi:10.22034/jipm.2025.2062799.2030

Design and Evaluation of Electronic Business Ontology Based on Persian Language Processing

Document Type : Original Article

Author

hamid ahmadi

PhD in Knowledge and Information Science; Assistant Professor; Department of Knowledge and Information Science; Faculty of Social Sciences; Razi University; Kermanshah

10.22034/jipm.2025.2062799.2030

Abstract

Ontology is a method of knowledge organization that establishes a coherent structure by defining concepts and their interrelationships. In the domain of Persian e-business, the absence of a native framework for data management and integration poses a significant challenge. To address this issue, this study aimed to design and develop an ontology in OWL (Web Ontology Language) with a specific focus on Persian language processing. A conceptual model was constructed, incorporating class hierarchies and semantic relationships, followed by an evaluation of its accuracy. The proposed ontology has the potential to enhance e-business performance by improving knowledge management and facilitating decision-making processes.
This applied research adopted a domain analysis approach. To construct the ontology, key concepts were first extracted from unstructured Persian texts using word co-occurrence analysis and the C-value technique. Hierarchical relationships were validated through a Delphi survey involving 10 domain experts. The conceptual model was then implemented in Protégé, formalized in OWL, and evaluated through expert feedback using descriptive statistics to assess the accuracy and validity of three types of semantic relations.
The study identified 141 concepts, categorized into 5 main classes and 136 subclasses. Additionally, 406 data attributes were defined across 17 data types and 34 object properties. Semantic relations were classified into three types: data properties, object properties, and interpretative relations, encompassing functional, symmetric, and transitive characteristics. Evaluation of the model revealed an average accuracy of 83.1% for semantic relations, with object properties scoring the highest (85.1%) and data properties the lowest (75.1%).
The findings demonstrate the structural coherence of the model and underscore the effectiveness of combining Persian text analysis with expert input. The developed ontology offers a robust foundation for standardizing and organizing knowledge within the Persian e-business domain. Limitations include weaker data property definitions and a lack of practical implementation examples. The primary contribution of this research lies in establishing a framework for logical inference within the Persian semantic web, providing a novel tool for researchers and startups. Its innovation stems from a dedicated focus on Persian language processing and the development of a native model an approach that has been underexplored in prior studies.

Keywords

Ontology, Electronic Business, Electronic Commerce, Knowledge Engineering, Web Technology, Semantic Web

Subjects

E-business

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