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Graphs are widely used to represent many differentkinds of real world data such as social networks, protein-proteininteractions, and road networks. In many cases, each node in agraph is associated with a set of its attributes and it is criticalto not only consider the link structure of a graph but also usethe attribute information to achieve more meaningful results invarious graph mining tasks. Most...
In ensemble learning, ensemble pruning is a procedure that aims at removing the unnecessary base classifiers and retaining the best subset of the base classifiers. We presented a two-step ensemble pruning framework, in which the optimal size of the pruned ensemble is first decided, and then with the optimal size as input, the optimal ensemble is selected. For the first step to find the optimal ensemble...
Many kinds of real world data can be modeled by a heterogeneous information network (HIN) which consists of multiple types of objects. Clustering plays an important role in mining knowledge from HIN. Several HIN clustering algorithms have been proposed in recent years. However, these algorithms suffer from one or moreof the following problems: (1) inability to model general HINs, (2) inability to...
We investigate where and how key dependency structure between measures of network activity change throughout the course of daily activity. Our approach to data-mining is probabilistic in nature, we formulate the identification of dependency patterns as a regularised statistical estimation problem. The resulting model can be interpreted as a set of time-varying graphs and provides a useful visual interpretation...
Skypatterns are an elegant answer to the pattern explosion issue, when a set of measures can be provided. Skypatterns for all possible measure combinations can be explored thanks to recent work on the skypattern cube. However, this leads to too many skypatterns, where it is difficult to quickly identify which ones are more important. First, we introduce a new notion of pattern steadiness which measures...
This paper focuses on the identification of overlapping communities, allowing nodes to simultaneously belong to several communities, in a decentralised way. To that aim it proposes LOCNeSs, an algorithm specially designed to run in a decentralised environment and to limit propagation, two essential characteristics to be applied in mobile networks. It is based on the exploitation of the preferential...
In this paper, we look at a mini version of NTRU public key cryptosystem which uses binary polynomials. Mini-NTRU uses smaller parameter sets while maintaining the original structure of NTRU, with the sole purpose of enabling undergraduate and graduate students who have basic cryptography knowledge understand the basic principles of NTRU operation. Once these basic principles are grasped, they can...
A signed graph is a graph obtained by giving signs to its edges. In this paper, we settle the problem of embedding (i, j)-regular signed graphs in (i + k, j + l)-regular signed graphs with the minimum number of vertices.
This study investigates students' industrial training experience and explores the ways to possibly enhance students' training experience. The findings show that providing more related information to students will definitely help them in gaining better training experience.
In this paper, we introduce computer vision to the study of gender politics and present a data-driven method to measure the impact of the ‘woman card’ exchange between Hillary Clinton and Donald Trump. Building from a unique dataset of the two candidates' Twitter followers, we first examine the transition dynamics of the two candidates' Twitter followers one week before the exchange and one week after...
A Router's syslogs are a sequence of events observed and logged by the router. They have been widely used in the system security field. This paper focuses on detecting anomalous behaviors of routers by analyzing router syslogs. For syslog data pre-processing, hierarchical clustering based on counting cousin distance between event patterns is used to cluster events. In order to construct a time series,...
Graph mining is widely used in fields like social network analysis. The synchronous vertex-centric frameworks strike better balance between the performance and ease-of-use, so they are widely used in realistic. However, traditional architectures of this type, like the vertex-based push architecture and GAS, are encumbered by high communication costs. In this paper we proposed a new replica-based push...
Access latency is a crucial performance metric in distributed storage systems as it greatly impacts user experience, especially for hot data visitors. Existing papers argue that coding can reduce access latency compared with the replication method, and many dispatch schemes, such as those implementing redundant requests, dynamically changing code rates, and so on, are proposed and proved to work well...
It is challenging to execute an application in a heterogeneous cloud cluster, which consists of multiple types of virtual machines with different performance capabilities and prices. This paper aims to mitigate this challenge by proposing a scheduling mechanism to optimise the execution of Bag-of-Task jobs on a heterogeneous cloud cluster. The proposed scheduler considers two approaches to select...
Finding repeated patterns or motifs in a time series is an important unsupervised task that has still a number of open issues, starting by the definition of motif. In this paper, we revise the notion of motif support, characterizing it as the number of patterns or repetitions that define a motif. We then propose GENMOTIF, a genetic algorithm to discover motifs with support which, at the same time,...
Acquiring the knowledge about the relationship among friendship network properties and check-in behavior of users (connected in the friendship network) has several benefits such as planning advertising strategies and recommending the friends or places. This paper aims to find the impact of structural patterns hidden in the nodes of a friendship network and external environment changes in the check-in...
Adapting systems to the changes of their ubiquitous environments is a complex task. The autonomic computing was proposed as a solution to tackle this complexity. It brings a system with self-management capabilities to dynamically adapt itself to context. We are interested in the architectural adaptation approaches of autonomic applications which follow the MAPE-K loop process. During the execution...
The study of compound-target binding profiles has been a central theme in cheminformatics. For data repositories that only provide positive binding profiles, a popular assumption is all unreported profiles are negative. In this paper, we caution audience not to take such assumption for granted. Under a problem setting where binding profiles are used as features to train predictive models, we present...
The backward observability (BO) of a part of the vector of trajectories of the system state is tackled for a general class of linear time-delay descriptor systems with unknown inputs. By following a recursive algorithm, we present easy testable sufficient conditions ensuring the BO of descriptor time-delay systems.
This paper studies stability of interconnections of hybrid dynamical systems, in the general scenario that the continuous or discrete dynamics of subsystems may have destabilizing effects. We analyze two existing methods of constructing Lyapunov functions for the interconnection based on candidate ISS Lyapunov functions for subsystems, small-gain conditions, and auxiliary timers modeling restrictions...
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