• M.LALITHA
• M.LALITHA SHARMA

This paper delves into the realm of domain-based network analysis, employing innovative approaches to unravel the complexities within four diverse domains: Literature Network, Ball Passing Network, Road Traffic Network, and Biomedical Network. Each domain encapsulates a unique set of challenges and opportunities, making them distinct arenas for network analysis with significant implications in various fields. The Literature Network domain serves as a fascinating canvas for exploring character relationships within narratives. Leveraging graph theory, characters become nodes, and their interactions form edges. The temporal aspect is introduced by analyzing different acts or chapters, creating a time-framed network. Graph-centric measures offer a quantitative lens, allowing for a nuanced understanding of character dynamics. This approach contributes to literary studies by providing a structured methodology to dissect and visualize the intricate web of character relationships. In the Ball Passing Network of sports, the focus shifts to team dynamics in games like football or basketball. The passing of the ball between players is represented as a dynamic, weighted, and directed social network. Zone identification becomes pivotal for optimizing game performance, offering insights into strategic areas on the field. By treating players as nodes and their passes as edges, this network analysis provides a unique perspective on the intricate social interactions that unfold during a match. The Road Traffic Network domain addresses the challenges of urban transportation. Here, the emphasis is on optimal route identification and traffic management. Roads and junctions form a weighted network, where the physical distance and traffic capacity of road segments are considered. Routing algorithms play a crucial role in minimizing traffic jams, and crowdsourcing solutions enhance real-time traffic information. The paper explores how these network analyses contribute to reducing waiting times, increasing throughput, and preventing road accidents. In the Biomedical Network domain, Boolean models take center stage for analyzing gene regulatory networks. Boolean Networks and Probabilistic Boolean Networks offer a simplified yet powerful representation of genetic interactions. The paper explores the successful application of these models in describing real gene regulatory relations, associating network attractors with cellular phenotypes. Boolean logic becomes a tool not only for analysis but also for developing control strategies to shape desirable phenotypes and mitigate undesirable ones, offering promising avenues for biomedical research and therapeutic interventions. This paper unfolds a panorama of innovative ideologies in domain-based network analysis. It transcends disciplinary boundaries, offering insights into literature, sports, transportation, and biomedicine. The varied challenges and opportunities within each domain showcase the versatility and transformative potential of network analysis methodologies. As technology and analytical tools advance, these approaches are poised to revolutionize our understanding and application of networks in complex systems.

Domain-based network analysis, Literature Network, Ball Passing Network, Road Traffic Network, Biomedical Network, Character relationships, Game maker identification, Optimal route identification, Boolean models, Gene regulatory networks, Network analysis, Innovative approaches, Interdisciplinary studies, Sports analytics, Computational biology

"Innovating Ideologies in Domain-Based Network Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.k52-k57, July-2023, Available :http://www.jetir.org/papers/JETIR2307A07.pdf

"Innovating Ideologies in Domain-Based Network Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppk52-k57, July-2023, Available at : http://www.jetir.org/papers/JETIR2307A07.pdf