Compared to global community detection, local community detection aims to find communities that contain a given node. Therefore, it can be regarded as a specific and personalized community detection task. Local community detection algorithms based on modularity are widely studied and applied because of their concise strategies and prominent effects. However, they also face challenges, such as sensitivity to seed node selection and unstable communities. In this paper, a local community detection algorithm based on local modularity density is proposed. The algorithm divides the formation process of local communities into a core area detection stage and a local community extension stage according to community tightness based on the Jaccard coefficient. In the core area detection stage, the modularity density is used to ensure the quality of the communities. In the local community extension stage, the influence of nodes and the similarity between the nodes and the local community are utilized to determine boundary nodes to reduce the sensitivity to seed node selection. Experimental results on real and artificial networks demonstrated that the proposed algorithm can detect local communities with high accuracy and stability.
Nano Research - Candida albicans (C. albicans) infection has a high mortality rate in immunocompromised patients. Owing to the inefficiency of the current diagnostic system and the absence of... 相似文献
Concomitance of diverse synaptic plasticity across different timescales produces complex cognitive processes. To achieve comparable cognitive complexity in memristive neuromorphic systems, devices that are capable of emulating short‐term (STP) and long‐term plasticity (LTP) concomitantly are essential. In existing memristors, however, STP and LTP can only be induced selectively because of the inability to be decoupled using different loci and mechanisms. In this work, the first demonstration of truly concomitant STP and LTP is reported in a three‐terminal memristor that uses independent physical phenomena to represent each form of plasticity. The emerging layered material Bi2O2Se is used for memristors for the first time, opening up the prospects for ultrathin, high‐speed, and low‐power neuromorphic devices. The concerted action of STP and LTP allows full‐range modulation of the transient synaptic efficacy, from depression to facilitation, by stimulus frequency or intensity, providing a versatile device platform for neuromorphic function implementation. A heuristic recurrent neural circuitry model is developed to simulate the intricate “sleep–wake cycle autoregulation” process, in which the concomitance of STP and LTP is posited as a key factor in enabling this neural homeostasis. This work sheds new light on the development of generic memristor platforms for highly dynamic neuromorphic computing. 相似文献