Organization 发表于 2025-3-28 15:22:14
Aggregate Distance Based Clustering Using Fibonacci Series-FIBCLUS global score is calculated for each instance using the novel idea of Fibonacci series. The use of Fibonacci numbers is able to separate the instances effectively and, in hence, the intra-cluster similarity is increased and the inter-cluster similarity is decreased during clustering. The proposed FIHemiparesis 发表于 2025-3-28 18:48:16
Role Discovery for Graph Clusteringty-based methods are developed in the past decades. These methods may be called non-overlapping because they assume that a vertex belongs to one community. On the other hand, overlapping methods such as CPM, which assume that a vertex may belong to more than one community, have been drawing attentiostratum-corneum 发表于 2025-3-29 00:58:19
http://reply.papertrans.cn/103/10217/1021649/1021649_43.png包租车船 发表于 2025-3-29 03:17:43
Aggregate Distance Based Clustering Using Fibonacci Series-FIBCLUS global score is calculated for each instance using the novel idea of Fibonacci series. The use of Fibonacci numbers is able to separate the instances effectively and, in hence, the intra-cluster similarity is increased and the inter-cluster similarity is decreased during clustering. The proposed FIFeature 发表于 2025-3-29 08:15:05
http://reply.papertrans.cn/103/10217/1021649/1021649_45.pngLAVA 发表于 2025-3-29 11:25:22
Top-, Probabilistic Closest Pairs Query in Uncertain Spatial Databasesof finding probabilistic .closest pairs between two uncertain spatial datasets, namely, . (Top.-PCP) query, which has popular usages in real applications. Specifically, given two uncertain datasets in which each spatial object is modeled by a set of sample points, a Top.-PCP query retrieves the pair可行 发表于 2025-3-29 18:46:56
http://reply.papertrans.cn/103/10217/1021649/1021649_47.png删减 发表于 2025-3-29 21:02:38
http://reply.papertrans.cn/103/10217/1021649/1021649_48.pngAPNEA 发表于 2025-3-30 00:02:32
http://reply.papertrans.cn/103/10217/1021649/1021649_49.png抓住他投降 发表于 2025-3-30 06:39:37
Discrete Trajectory Prediction on Mobile Datat techniques only consider objects’ individual history or crowd movement alone. In practice, either individual history or crowd movement is not enough to predict trajectory with high accuracy. In this paper, we focus on how to predict fragmental trajectory. Based on the discrete trajectory obtained