Zobrazeno 1 - 10
of 1 998
pro vyhledávání: '"dynamic graph"'
Autor:
Cho Do Xuan, Tung Thanh Nguyen
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract To enhance the effectiveness of the Advanced Persistent Threat (APT) detection process, this research proposes a new approach to build and analyze the behavior profiles of APT attacks in network traffic. To achieve this goal, this study carr
Externí odkaz:
https://doaj.org/article/8adc37f10081473ca0b8cb6b1cce9073
Autor:
Zi-chao Chen, Sui Lin
Publikováno v:
Autonomous Intelligent Systems, Vol 4, Iss 1, Pp 1-12 (2024)
Abstract The integration of Dynamic Graph Neural Networks (DGNNs) with Smart Manufacturing is crucial as it enables real-time, adaptive analysis of complex data, leading to enhanced predictive accuracy and operational efficiency in industrial environ
Externí odkaz:
https://doaj.org/article/7523802c8a044ec9887db49b467d4ea6
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 9, Pp 102202- (2024)
Extracting structured information from unstructured text is crucial for knowledge management and utilization, which is the goal of document-level relation extraction. Existing graph-based methods face issues with information confusion and integration
Externí odkaz:
https://doaj.org/article/1aeed0c0844340e99e011a046b132072
Publikováno v:
PeerJ Computer Science, Vol 10, p e2361 (2024)
Frequent subgraph mining (FSM) is an essential and challenging graph mining task used in several applications of the modern data science. Some of the FSM algorithms have the objective of finding all frequent subgraphs whereas some of the algorithms f
Externí odkaz:
https://doaj.org/article/adf9017876054ccaaa8f05d3589299e1
Publikováno v:
IEEE Access, Vol 12, Pp 43460-43484 (2024)
In recent years, Dynamic Graph (DG) representations have been increasingly used for modeling dynamic systems due to their ability to integrate both topological and temporal information in a compact representation. Dynamic graphs efficiently handle ap
Externí odkaz:
https://doaj.org/article/68b5a75fc99d41acba6d686853a58977
Autor:
Zhiwen Hou, Fanliang Bu, Yuchen Zhou, Lingbin Bu, Qiming Ma, Yifan Wang, Hanming Zhai, Zhuxuan Han
Publikováno v:
Mathematical Biosciences and Engineering, Vol 21, Iss 3, Pp 3563-3593 (2024)
Dynamic recommendation systems aim to achieve real-time updates and dynamic migration of user interests, primarily utilizing user-item interaction sequences with timestamps to capture the dynamic changes in user interests and item attributes. Recent
Externí odkaz:
https://doaj.org/article/7bd5dfe9de6f453883691be587505d82
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 19003-19015 (2024)
Sea surface temperature (SST) plays a crucial role in the global meteorological system, particularly as long-term seasonal variations are significant for analyzing SST anomalies and supporting long-term climate decision-making. Current forecasting me
Externí odkaz:
https://doaj.org/article/18f6a1f06839498d9bdead94cec06c58
Publikováno v:
IEEE Access, Vol 12, Pp 131664-131680 (2024)
Currently, video question answering (VideoQA) algorithms relying on video-text pretraining models employ intricate unimodal encoders and multimodal fusion Transformers, which often lead to decreased efficiency in tasks such as visual reasoning. Conve
Externí odkaz:
https://doaj.org/article/602c42a43f134051b839978976c02118
Autor:
Elena Tiukhova, Emiliano Penaloza, Maria Oskarsdottir, Bart Baesens, Monique Snoeck, Cristian Bravo
Publikováno v:
IEEE Access, Vol 12, Pp 115026-115041 (2024)
Leveraging network information for predictive modeling has become widespread in many domains. Within the realm of referral and targeted marketing, influencer detection stands out as an area that could greatly benefit from the incorporation of dynamic
Externí odkaz:
https://doaj.org/article/c996a016d3834582aec98711905b9e24
Autor:
Chien-Chou Lin, Po-Yu Chen
Publikováno v:
IEEE Access, Vol 12, Pp 111924-111931 (2024)
Recently, deep learning neural networks have been widely used in object classification. The process of object classification typically involves extracting features from the point cloud using neural networks and integrating these features into a globa
Externí odkaz:
https://doaj.org/article/e6c16ed6d50649a4aeac53e3a0f9ee8a