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With the number of smartphone applications (apps) growing explosively, it has a practical significance to provide personalized app recommendations. In this paper, we propose the GTRM, a new recommendation model which builds the top-N app list by optimizing the metric Group-oriented Mean Average Precision (GMAP). GMAP is an extension of the traditional metric Mean Average Precision (MAP) and it measures...
Resource performance prediction has become more and more important in cloud environment as CPU load prediction is key for system maintenance and application schedule. This paper presents a multidimensional spatial voting prediction model to predict real-time CPU load accurately. We improved the real-time CPU load prediction accuracy by gray prediction model under the one-dimension prediction, we also...
Keyword extraction aims to find representative phrases for a document. Graph-based keyword extraction represent the input document as a graph and rank its nodes according to their score using graph-based ranking method. In this paper, we propose a method to compute importance of co-occurrence word in document and apply it in graph approach to find more representative phrases; introduce words correlation...
As modern computer systems become increasingly complex in infrastructure and usage, the demand for capabilities of detecting anomalous behavior has grown urgent. Although techniques for point anomaly detection have been proposed and adopted in practice, behavior anomaly detection still lacks effective approaches due to its inherent complexities. We present a new anomalous behavior detection model...
Cloud computing provides an efficient way to expose computing capabilities as sophisticated services that can be accessed remotely. It eliminates the need for organizations to maintain extensive infrastructures. Parallel and distributed simulation over cloud will bring us not only the increased productivity and efficiency but also the lower barrier for usage. This paper introduces a private cloud...
In the past few decades, large-scale distributed computing systems such as grids have been widely used to serve a growing number of applications in a time-shared manner. In such environment, resources should be strictly assigned to achieve high performance. Hence, resource monitoring and usage prediction are required for the scheduling. Among these resources, CPU load has a significant effect on the...
In order to better support service collaboration for complex tasks, an event view model is proposed to facilitate the activation and integration of individual service processes. An event view is composed of a set of event types and their dependency relationships, it provides a public view of a service process model and serves as the basis for defining process collaboration protocols. After discussing...
Service process has been increasingly adopted in various domains with the development of service computing. As more and more service processes come to have complex business logic for changing business requirements, service process must have the ability to configure itself automatically in a certain business context. In this paper, we provide an approach to realize service process's self-configuration...
This paper presents a novel method for recognizing objects using corner features. As one of the most important local features, corner contains lots of information with the shape of the objects. Our approach detects corner points from images and describes the objects based on them. The features are highly distinctive, in the sense that a single feature can be correctly matched with high probability...
Grid computing technology makes it possibly to use scientific workflow to be shared and reused among different users. However, a scientific workflow model usually needs to be tailored during reuse because of different problem contexts met by different users. These change logs provide additional information to help users customize scientific workflow. In this paper, we present a change sequence mining...
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