Zobrazeno 1 - 10
of 298
pro vyhledávání: '"Attributed networks"'
Publikováno v:
Big Data Mining and Analytics, Vol 7, Iss 3, Pp 794-808 (2024)
Attributed graphs have an additional sign vector for each node. Typically, edge signs represent like or dislike relationship between the node pairs. This has applications in domains, such as recommender systems, personalised search, etc. However, lim
Externí odkaz:
https://doaj.org/article/c9b18aab5ace49698fb45e624bd6185c
Autor:
Wasim Khan, Shafiqul Abidin, Mohammad Arif, Mohammad Ishrat, Mohd Haleem, Anwar Ahamed Shaikh, Nafees Akhtar Farooqui, Syed Mohd Faisal
Publikováno v:
Data Science and Management, Vol 7, Iss 2, Pp 89-98 (2024)
Many types of real-world information systems, including social media and e-commerce platforms, can be modelled by means of attribute-rich, connected networks. The goal of anomaly detection in artificial intelligence is to identify illustrations that
Externí odkaz:
https://doaj.org/article/904353bd8a6e4d10bd5ac9cb2fa3dd5c
Autor:
Wasim Khan, Mohammad Ishrat, Ahmad Neyaz Khan, Mohammad Arif, Anwar Ahamed Shaikh, Mousa Mohammed Khubrani, Shadab Alam, Mohammed Shuaib, Rajan John
Publikováno v:
IEEE Access, Vol 12, Pp 65555-65569 (2024)
Attributed networks are prevalent in the current information infrastructure, where node attributes enhance knowledge discovery. Anomaly detection in attributed networks is gaining attention for its potential uses in cybersecurity, finance, and health
Externí odkaz:
https://doaj.org/article/1053626ae17c4fdcb5f75ae134caf91e
Publikováno v:
Applied Network Science, Vol 8, Iss 1, Pp 1-27 (2023)
Abstract We investigate the statistical learning of nodal attribute functionals in homophily networks using random walks. Attributes can be discrete or continuous. A generalization of various existing canonical models, based on preferential attachmen
Externí odkaz:
https://doaj.org/article/11a32c9656f24ad3a1d20dabe6294f69
Publikováno v:
Applied Network Science, Vol 8, Iss 1, Pp 1-19 (2023)
Abstract Recent advances in network science have resulted in two distinct research directions aimed at augmenting and enhancing representations for complex networks. The first direction, that of high-order modeling, aims to focus on connectivity betw
Externí odkaz:
https://doaj.org/article/5f950a496ce14982ba5d4aaea1e28eb0
Publikováno v:
Applied Sciences, Vol 14, Iss 6, p 2356 (2024)
Community detection in social networks is of great importance and is used in a variety of applications such as recommendation systems and targeted advertising. While detecting dense groups with high levels of connectivity and similar interests betwee
Externí odkaz:
https://doaj.org/article/5f32fa566da547929cb9ae70cce38c45
Akademický článek
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Publikováno v:
Applied Network Science, Vol 7, Iss 1, Pp 1-44 (2022)
Abstract Graph representation learning has become a topic of great interest and many works focus on the generation of high-level, task-independent node embeddings for complex networks. However, the existing methods consider only few aspects of networ
Externí odkaz:
https://doaj.org/article/10405bf9b9fa43ef86239d9a1bd2da2e
Autor:
Wasim Khan, Mohammad Haroon
Publikováno v:
International Journal of Cognitive Computing in Engineering, Vol 3, Iss , Pp 153-160 (2022)
Due to its importance in several applications, including fraud and spammer detection, anomaly detection has emerged as a key challenge in social network analysis in recent years. By including both graph and node properties, aberrant nodes in static a
Externí odkaz:
https://doaj.org/article/c0a14925b75442cebf4ef83261f35a23
Autor:
Wasim Khan, Mohammad Haroon, Ahmad Neyaz Khan, Mohammad Kamrul Hasan, Asif Khan, Umi Asma Mokhtar, Shayla Islam
Publikováno v:
IEEE Access, Vol 10, Pp 91160-91176 (2022)
A significant aspect of today’s digital information is attributed networks, which combine multiple node attributes with the basic network topology to extract knowledge. Anomaly Detection on attributed networks has recently drawn significant attenti
Externí odkaz:
https://doaj.org/article/93e0e6ab6a674e3989f9079de7322ef9