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Network structure has been used to describe many systems in the real world. Nodes, which represent the units, and edges, which represent the connection of the units constitute the network structure. The monitoring of the Peer-to-Peer (P2P) networks can also be described by the general network model. In this paper, we provide an algorithm to divide network based on the social network analysis. By calculating...
Link prediction is a fundamental task for analyzing complex networks which has been widely used in many domains, such as, identify spurious interactions, extract missing information, evaluate complex network evolving mechanism. There exist a variety of techniques for link prediction, ranging from node similarity-based methods to probabilistic graphical models. Node similarity-based methods have low...
Link prediction is an important issue in social network analysis. It aims at estimating the likelihood of the existence of links between nodes by the known network information. Although this problem has been extensively studied, many significant factors about how to calculate the similarity between two nodes remains unexplored and largely open, especially for the mobile phone networks. We are first...
Decentralized search in networks is an important algorithmic problem in the study of complex networks and social networks analysis. It has a large number of practical applications, from shortest paths search in social network relationship, web pages search in WWW to querying files in peer-to-peer file sharing networks and so on. In this paper, we explore this problem from a perspective of community...
Community detection, as an important unsupervised learning problem in social network analysis, has attracted great interests in various research areas. Many objective functions for community detection that can capture the intuition of communities have been introduced from different research fields. Based on the classical single objective optimization framework, this paper compares a variety of these...
Along with informationization advancement thorough and Internet rapid development, there exists millions of websites on the Internet. Search engines become a mediator to connect web users and websites. The query logs in which recorded daily contains a wealth of knowledge about the actions of the users of search engines, and as such they contain valuable information about the interests, the preferences,...
Recently, a growing number of researches have focused on the issues raised by the knowledge discovery of online information, particularly the problems of tracking topics, ideas, and users' spreading influence across the Web. In this paper, the search-engine query logs on Topic Detection and Tracking (TDT) is analyzed other than study of the quality of the search result or query recommendation. By...
With the emergence of massive social media, massive social networks have led to a huge interest in data analysis. In this paper, we propose an empirical study on several massive social networks including 4 mobile call graphs, a fixed-line call graph, two co-authorship networks and two Email networks. We find that call graphs tend to be more locality than the co-authorship networks and Email networks...
Researches have discovered that rich interactions among entities in nature and human society bring about complex networks with community structures. In this paper, we propose a novel algorithm BiTector (bi-community detector) to mine the overlapping communities in large-scale sparse bipartite networks. We apply the algorithm to various real-world datasets, showing that BiTector can identify the overlapping...
An interesting property of network is that the information is not only contained in the entities, but also in the links between them. As the structure of the co-authorship network can greatly influence its function and reflect how the internal information is exchanged. We attempt to get deep insight of the features in a co-authorship network at a university. This is done by the following two steps...
As acquiring and retaining the most profitable customers are challenging tasks of service providers, various CRM tools are used to support these processes. Traditional CRM methods focus on various customer profitability models in different scenarios based on their past profit contribution. Social network analysis provides a natural way to understand the relationships between customers; however, this...
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