Weighted Community Detection and Data Clustering Using Message Passing
نویسندگان
چکیده
Cheng Shi, Yanchen Liu and Pan Zhang3∗ CompleX Lab, Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 611731, Peoples Republic of China Network Science Institute, Northeastern University, 177 Huntington Avenue, Boston, MA, 02115, United States of America CAS key laboratory of theoretical physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China (Dated: January 31, 2018)
منابع مشابه
Data Streaming with Affinity Propagation
This paper proposed StrAP (Streaming AP), extending Affinity Propagation (AP) to data steaming. AP, a new clustering algorithm, extracts the data items, or exemplars, that best represent the dataset using a message passing method. Several steps are made to build StrAP. The first one (Weighted AP) extends AP to weighted items with no loss of generality. The second one (Hierarchical WAP) is conce...
متن کاملWeighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information
We study the misclassification error for community detection in general heterogeneous stochastic block models (SBM) with noisy or partial label information. We establish a connection between the misclassification rate and the notion of minimum energy on the local neighborhood of the SBM. We develop an optimally weighted message passing algorithm to reconstruct labels for SBM based on the minimu...
متن کاملOnline Community Detection by Using Nearest Hubs
Community and cluster detection is a popular field of social network analysis. Most algorithms focus on static graphs or series of snapshots. In this paper we present an algorithm, which detects communities in dynamic graphs. The method is based on shortest paths to high-connected nodes, so called hubs. Due to local message passing we can update the clustering results with low computational pow...
متن کاملSparse Message Passing Algorithms for Weighted Maximum Satisfiability
Weighted maximum satisfiability is a wellstudied problem that has important applicability to artificial intelligence (for instance, MAP inference in Bayesian networks). General-purpose stochastic search algorithms have proven to be accurate and efficient for large problem instances; however, these algorithms largely ignore structural properties of the input. For example, many problems are highl...
متن کاملتشخیص اجتماعات ترکیبی در شبکه‌های اجتماعی
One of the great challenges in Social Network Analysis (SNA) is community detection. Community is a group of vertices which have high intra connections and sparse inter connections. Community detection or Clustering reveals community structure of social networks and hidden relationships among their constituents. By considering the increase of datasets related to social networks, we need scalabl...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- CoRR
دوره abs/1801.09829 شماره
صفحات -
تاریخ انتشار 2018