Efficient Personalized Community Detection via Genetic Evolution
Personalized community detection aims to generate communities associated with user need on graphs, which benefits many downstream tasks such as node recommendation and link prediction for users, etc. It is of great importance but lack of enough attention in previous studies which are on topics of user-independent, semi-supervised, or top-K user-centric community detection. Meanwhile, most of their models are time consuming due to the complex graph structure. Different from these topics, personalized community detection requires to provide higher-resolution partition on nodes that are more relevant to user need while coarser manner partition on the remaining less relevant nodes. In this paper, to solve this task in an efficient way, we propose a genetic model including an offline and an online step. In the offline step, the user-independent community structure is encoded as a binary tree. And subsequently an online genetic pruning step is applied to partition the tree into communities. To accelerate the speed, we also deploy a distributed version of our model to run under parallel environment. Extensive experiments on multiple datasets show that our model outperforms the state-of-arts with significantly reduced running time.
Code (0)
등록된 구현이 없습니다.
Tasks
Community DetectionLink PredictionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Transfer Learning Based Multi-Objective Genetic Algorithm for Dynamic Community Detection
Dynamic community detection is the hotspot and basic problem of complex network and artificial intelligence research in recent years. It is necessary to maximize the accuracy of clustering as the network structure change…
ClusteringCommunity DetectionDynamic Community DetectionEvolutionary Algorithms+1Effects of phylogeny on coexistence in model communities
Species' interactions are shaped by their traits. Thus, we expect traits -- in particular, trait (dis)similarity -- to play a central role in determining whether a particular set of species coexists. Traits are, in turn,…
Phylogenetic reconstruction of the cultural evolution of electronic music via dynamic community detection (1975-1999)
Cultural phylogenies, or "trees" of culture, are typically built using methods from biology that use similarities and differences in artifacts to infer the historical relationships between the populations that produced t…
Community DetectionCultural Vocal Bursts Intensity PredictionDiversityDynamic Community DetectionEvolutionary Multi Objective Optimization Algorithm for Community Detection in Complex Social Networks
Most optimization-based community detection approaches formulate the problem in a single or bi-objective framework. In this paper, we propose two variants of a three-objective formulation using a customized non-dominated…
Community DetectionDetecting Communities in Complex Networks using an Adaptive Genetic Algorithm and node similarity-based encoding
Detecting communities in complex networks can shed light on the essential characteristics and functions of the modeled phenomena. This topic has attracted researchers of various fields from both academia and industry. Am…
Community Detection