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The popularity of cloud service spurs the increasing demands of cloud resources to the cloud service providers. Along with the new business opportunities, the pay-as-you-go model drastically changes the usage pattern and brings technology challenges to effective capacity planning. In this paper, we propose a new method for cloud capacity planning with the(More)
The promise of cloud computing is to provide computing resources instantly whenever they are needed. The state-of-art virtual machine (VM) provisioning technology can provision a VM in tens of minutes. This latency is unacceptable for jobs that need to scale out during computation. To truly enable on-the-fly scaling, new VM needs to be ready in seconds upon(More)
The popularity of cloud service spurs the increasing demands of virtual resources to the service vendors. Along with the promising business opportunities, it also brings new technique challenges such as effective capacity planning and instant cloud resource provisioning. In this paper, we describe our research efforts on improving the service quality for(More)
The advent of Big Data era drives data analysts from different domains to use data mining techniques for data analysis. However, performing data analysis in a specific domain is not trivial; it often requires complex task configuration, onerous integration of algorithms, and efficient execution in distributed environments.Few efforts have been paid on(More)
Modern scientific databases and web databases maintain large and heterogeneous data. These real-world databases contain hundreds or even thousands of relations and attributes. Traditional predefined query forms are not able to satisfy various ad-hoc queries from users on those databases. This paper proposes DQF, a novel database query form interface, which(More)
The cold-start problem has attracted extensive attention among various online services that provide personalized recommendation. Many online vendors employ contextual bandit strategies to tackle the so-called <i>exploration/exploitation</i> dilemma rooted from the cold-start problem. However, due to high-dimensional user/item features and the underlying(More)
Anomaly detection has always been a critical and challenging problem in many application areas such as industry, healthcare, environment and finance. This problem becomes more dicult in the Big Data era as the data scale increases dramatically and the type of anomalies gets more complicated. In time sensitive applications like real time monitoring , data(More)
Advanced manufacturing such as aerospace, semi-conductor, and flat display device often involves complex production processes, and generates large volume of production data. In general, the production data comes from products with different levels of quality, assembly line with complex flows and equipments, and processing craft with massive controlling(More)
Event mining is a useful way to understand computer system behaviors. The focus of recent works on event mining has been shifted to event summarization from discovering frequent patterns. Event summarization seeks to provide a comprehensible explanation of the event sequence on certain aspects. Previous methods have several limitations such as ignoring(More)