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The target of many studies in the health sciences is the discovery of cause-effect relationships among observed variables of interest, for example: treatments, exposures, preconditions, and outcomes. Causal modeling and causal discovery are central to medical science. In order to algorithmically consider causal relations, the relations must be placed into a representation that supports manipulation...
This paper presents a novel method to estimate characteristics of information sources about a topic by analyzing their information diffusion subnetworks in blogspace. In an information diffusion network, each influential information source has an affected subnetwork whose nodes are reachable from it. We define three information diffusion properties of the subnetwork using the numbers of three types...
In an organization, based on the positions of employees there is usually an existing hierarchy among them. However, in real-life cases, people's interactions tend to form a certain communication structure due to some external forces or personal factors. In this paper, we aim at discovering the potential communication structure, in which nodes are typed labels (e.g. job-titles) and edges stand for...
A qualitative way is desirable for web service selection according to agents' preferences on non-functional Quality of Service (QoS) attributes of services. However, it is challenging when the decision has to be made for multiple agents with preferences on attributes that may be incomplete. In this paper, we first use a qualitative graphical representation tool called CP-nets to describe preference...
Many real world phenomena can be naturally modeled as graph structures whose nodes representing entities and whose edges representing interactions or relationships between entities. The analysis of the graph data have many practical implications. However, the release of the data often poses considerable privacy risk to the individuals involved. In this paper, we address the edge privacy problem in...
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