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Documents in many corpora, such as digital libraries and webpages, contain both content and link information. In a traditional topic model which plays an important role in the unsupervised learning, the link information is either totally ignored or treated as a feature similar to content. We believe that neither approach is capable of accurately capturing the relations represented by links. To address...
In this paper, we present our analysis of resource scheduling to achieve SLA-aware profit optimization in cloud services. This work is part of a real system called Intelligent Cloud Database Coordinator (ICDC), which is being built at the NEC Labs to manage very large cloud service delivery infrastructures. As we present in our performance evaluation, the analysis shows that the choice of resource...
The limitation of natural parallelization comes from data management. Ever increasing need for scalability and new data and applications create new challenges for relational database systems. Different business needs and workloads may be satisfied with diverse set of data management capabilities. More importantly the business needs also evolve over the time by making existing implementations obsolete...
Knowledge discovery from scientific articles has received increasing attentions recently since huge repositories are made available by the development of the Internet and digital databases. In a corpus of scientific articles such as a digital library, documents are connected by citations and one document plays two different roles in the corpus: document itself and a citation of other documents. In...
As the amount of noisy, unorganized, linked data on the Internet increases dramatically, how to efficiently analyze such data becomes a challenging research problem. In this paper, we propose a framework, iOLAP, that offers functionalities for analyzing networked data from Internet, social networks, scientific paper citations, etc. We first identify four main data dimensions that are common in most...
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