Morteza Mohammadi Ostani, Ph.D. ,

Assistant Professor

Department Of Knowledge And Information Science
Faculty Of Education And Psychology

Email

m.ostani@edu.ui.ac.ir

Phone

37935836

Address

University of Isfahan Azadi square Isfahan, Iran
Postal Code : 8174673441

Overview

Research Interests

My favorite research is search engine interoperability, ontology, knowledge management and knowledge organization in general. Research has also been conducted in the field of public libraries and related issues.

Memberships

Member of the Iranian Library and Information Science Association (ILISA) Member of the Iranian Public Library Promotion Association (IPLPA) Member of the National Elite Foundation

Professional activities

Knowledge and Information Organization and Management Ontology and Thesaurus Document Organization Public Libraries

Education

Ph.D., Designing microdata schema for Iranian-Islamic information context's manuscripts and studying the reaction of web search engines to the records based on that schema, University of Isfahan [Isfahan - Iran]
Master's degree, A Feasibility Study for Implementing Knowledge Management in the Academic Libraries of Isfahan City based on Bukowitz and William’s Model, University of Isfahan [Isfahan - Iran]

Research Output

All

Article

Articles

2024

Using Conceptual Clustering to Extraction of Key Phrases and Related Terms: A Case Study of Scientific Communication Texts

( Article . )

Shahvandi, R.K., Shabani, A., Asemi, A., Mohammadi ostani, M.

Publication Date: 2024/06/21

Iranian Journal of Information Processing and Management (22518223)39(4)pp. 1443-1475

Scientific communication encompasses various types and forms of communication conducted through the use of communication methods and tools, aiming to exchange scientific knowledge and information. To gain a comprehensive understanding of scientific and research communications and enhance them, it is crucial to identify the terms and concepts. Therefore, the main objective of this research is to identify and conceptually cluster key terms in the field of scientific communication using text mining techniques. The present research method is quantitative in terms of approach and practical in terms of purpose and utilized various text mining techniques for identifying and clustering key terms in the field of scientific communication. The research population consists of abstracts of articles related to scientific communication, extracted from databases such as Web of Science and Scopus, totaling 558 articles. The sampling method was census. Initially, all nominal phrases were extracted using available libraries. Each compound phrase was decomposed into its constituent words, and based on GloVe dictionary, the average vectors of those words were calculated, assigning a numerical vector to each compound phrase. The researchers created an equivalent expression using existing vocabulary to describe unknown terms that did not exist in the GloVe dictionary. The clustering (using the K-means method) was performed on these vectors. The findings revealed that out of 17,930 extracted keywords, 13,651 terms were noun phrases. Also, 16% of terms in the field of scientific communication were single words and 84% of them were compound. After creating vectors of compound terms and performing clustering, 40 conceptual clusters were created from 792 phrases or terms in the field of scientific communication. After adjusting and removing weak clusters, researchers finally identified 22 clusters in the field of scientific communication. Identifying the concepts and components in scientific communication in the form of conceptual clusters and its elements is attributed to the results of this research. One of the most significant findings was the assignment of numerical vectors to composite phrases based on the vectors of their constituent words. These vectors were then used for clustering and categorizing phrases, as well as improving and correcting some clusters. This method pays attention to the semantics aspects and learning in the clustering and categorization of concepts and, will aid to precise analysis of key terms and phrases in various fields.

2025