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Recently, every enterprise generates large volumes of high dimensional data on a regular basis. Complex data mining and analysis techniques are used to feasibly analyse this data. Feature selection aids in this by providing a reduced representation of this data while maintaining integrity. We propose a graph-based feature selection algorithm utilizing feature intercorrelation to construct a weighted...
Detection of hotspots (also known as dense subgraphs) in network data is an important data analysis problem due to it's significance in many contemporary applications. Clique-based formulation of this problem employing maximum flow implementation turns out to be an optimization task limiting the solution to be an approximate one. On the other hand, an iterative method building the hotspots (dense...
Mobile Social Network Analysis is the mapping and measuring of interactions and flows between people, groups, and organizations based on the usage of their mobile communication services. Social Network Analysis and Mining has been highly influenced by the online social web sites, telecom consumer data and instant messaging systems, and has widely analyzed the presence of dense communities using graph...
There has been growing interest in studying combinatorial optimization problems by clustering strategy, with a special emphasis on the traveling salesman problem (TSP). Since TSP naturally arises as a sub problem in many transportation, manufacturing and various logistics application, this problem has caught much attention of mathematicians and computer scientists. A clustering strategy will decompose...
Given a graph and an integer L ?? 0, the beacon placement problem (BPP) asks to find a minimum set B of nodes such that for all edges e, at least one of the two endpoints of e can be reached from some node (called an L-beacon) in B using at most L edges. In particular, it reduces to the vertex cover problem if L = 0. This problem arises from link-monitoring in computer networks. Generalizing the works...
The recent proliferation of graph data in a wide spectrum of applications has led to an increasing demand for advanced data analysis techniques. In view of this, many graph mining techniques, such as frequent subgraph mining and correlated subgraph mining, have been proposed. In many applications, both frequency and correlation play an important role. Thus, this paper studies a new problem of mining...
Information infrastructures such as Internet have been a great success in the past few decades and gradually become mature, diversified user requirements continue to grow at a fabulous speed. Multiplex services on secure networked environments are now deemed as an application licensed to customers for use as a trustworthy service on demand. The flexible reconfiguration network is the next step to...
Approximate solutions to labelling problems can be found using binary graph cuts and either the ??-?? expansion or ??-?? swap algorithms. In some specific cases, an exact solution can be computed by constructing a multilabel graph. However, in many practical applications the multilabel graph construction is infeasible due to its excessively large memory requirements. In this work, we expand the concept...
In this paper we investigate the influences on the genetic algorithm for the shortest driving time problem due to factors such as nodes on a map, the population size, the mutation rate, the crossover rate, and the converging rate. When the nodes on the map increase, more execution time is needed and much difference between the approximate solution and the exact solution appear on running genetic algorithms...
In order to plan the network construction reasonable and ensure the quality of network service, it is important to measure the Link-bandwidth utilization and get the flow information. One of the methods to monitor network efficiently is based on flow-conservation, and the problem of searching a solution for this method could be deduced to solving weak vertex cover problem, which has been proved NP-hard...
Designing appropriate graphs is a problem frequently occurring in several common applications ranging from designing communication and transportation networks to discovering new drugs. More often than not the graphs to be designed need to satisfy multiple, sometimes conflicting, objectives e.g. total length, cost, complexity or other shape and property limitations. In this paper we present our approach...
Protein binding sites are often represented by means of graphs capturing their most important geometrical and physicochemical properties. Searching for structural similarities and identifying functional relationships between them can thus be reduced to matching their corresponding graph descriptors. In this paper, we propose a method for the structural analysis of protein binding sites that makes...
In this article, the problem of finding maximum (weight) independent set (M(W)IS) is investigated. It is known that this problem belongs to the class of NP-hard problems. Although, there are polynomial time (P-time) algorithms to solve the M(W)IS problem for some special classes of graphs. Here, we propose a general scheme which extends all of classes that the M(W)IS problem is solvable for them in...
A novel graph-based approach to automatically refine image annotation is presented in this paper. Given an unannotated image, a set of candidate annotations is extracted by the existing image annotation method. Then, each candidate annotation is converted to vertex of a graph and the semantic similarity between two candidate annotations is used as edge weight. Next, a heuristics graph algorithm solving...
In this paper, we study distributed classification of targets in a large scale sensor network setting. Specifically, we consider sensor nodes which can measure only a part of the feature vector and whose communication capabilities are limited to only their neighbouring nodes. We formulate a distributed classification algorithm that learns the optimal (large-margin) hyperplane separating the two classes,...
Cognitive radios must be able to form collaborative wireless network clusters in dynamically changing environments to achieve such desired objectives as interference resilience and low communications overhead. In this work, we explore the affinity propagation (AP) message-passing technique to efficiently group nodes in an ad hoc cognitive radio network (CRN). With the proposed approach, nodes exchange...
This paper discusses the ranking of a set of objects when a possibly inconsistent set of pairwise preferences is given.We consider the task of ranking objects when pairwise preferences not only can contradict each other, but in general are not binary-meaning, for each pair of objects the preference is represented by a pair of non-negative numbers that sum up to one and can be viewed as a confidence...
Triangle counting is an important problem in graph mining. The clustering coefficient and the transitivity ratio,two commonly used measures effectively quantify the triangle density in order to quantify the fact that friends of friends tend to be friends themselves. Furthermore, several successful graph mining applications rely on the number of triangles. In this paper, we study the problem of counting...
As a typical social media in Web 2.0 era, blogs have become more and more important to information diffusion. Different from the traditional news, the information spread on blogs is primarily driven by users and their relations. According to this phenomenon, this paper addresses the novel problem of measuring the influence of social structures on information diffusion. This paper extracts the hidden...
The correlation clustering problem has been introduced recently as a model for clustering data when a binary relationship between data points is known. Correlation clustering is a graph-theoretic based clustering. More precisely, in a graph G = (V,E) vertices of the graph denote the number of items, where each edge of the graph labeled as either + or - depending upon the similarity or dissimilarity...
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