Themes-based classification for Al-Quran knowledge ontology

Al-Quran knowledge representations involved classification of Al-Quran verses for providing better understanding of the readers. In the current era of social media challenges. the representation of knowledge must be understood by human and computer in order to ensure the correctness of Al-Quran semantics are persevered.Current approaches used conventional methods such as taxonomy, hierarchy or tree structure, which only provides a concept definition without linked to other sources of knowledge explanation. This research aims to develop the Al-Quran Ontology by using theme-based classification approach.The ontology model for Al-Quran is developed based on the Al-Quran knowledge theme defined in Syammil Al-Quran Miracle the Reference.The theme-based ontology approach has shown that the Al-Quran knowledge can be classified and presented systematically.This will encourage the development of applications for Al-Quran readers.Moreover, the ontology structure that representing the theme concepts in Al-Quran was reviewed and validated by the domain experts in Al-Quran knowledge

A Comprehensive Bibliometric Analysis on Social Network Anonymization: Current Approaches and Future Directions

In recent decades, social network anonymization has become a crucial research field due to its pivotal role in preserving users' privacy. However, the high diversity of approaches introduced in relevant studies poses a challenge to gaining a profound understanding of the field. In response to this, the current study presents an exhaustive and well-structured bibliometric analysis of the social network anonymization field. To begin our research, related studies from the period of 2007-2022 were collected from the Scopus Database then pre-processed. Following this, the VOSviewer was used to visualize the network of authors' keywords. Subsequently, extensive statistical and network analyses were performed to identify the most prominent keywords and trending topics. Additionally, the application of co-word analysis through SciMAT and the Alluvial diagram allowed us to explore the themes of social network anonymization and scrutinize their evolution over time. These analyses culminated in an innovative taxonomy of the existing approaches and anticipation of potential trends in this domain. To the best of our knowledge, this is the first bibliometric analysis in the social network anonymization field, which offers a deeper understanding of the current state and an insightful roadmap for future research in this domain.Comment: 73 pages, 28 figure