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- W4386847280 abstract "In the past decades, complex networks have become an emanating area. It is applicable in diverse domains like technological, biological, and social networks and many other areas. Large networks comprise small communities and their detection is a recent field of research. Identification of various communities is important for better analysis of the network. Communities possess different natures like overlapping, hierarchical and a few others. Their detection depends on various factors such as size, nature, the complexity of the network and compatibility with the detection algorithm. The task is not only to segregate the communities but also to locate them as quickly as possible. There exists a number of techniques to complete this task. These algorithms possess their specific means for achieving this target. In this paper, an effort is made to analyze three different community detection algorithms based on their runtime and their working criteria. Execution of these algorithms with four well-known social networks is also demonstrated." @default.
- W4386847280 created "2023-09-20" @default.
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- W4386847280 date "2023-01-01" @default.
- W4386847280 modified "2023-09-27" @default.
- W4386847280 title "Analysis of Community Detection Algorithms with Social Networks" @default.
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- W4386847280 doi "https://doi.org/10.1007/978-981-99-3963-3_46" @default.
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