indoor radon concentration (irc) is among the emerging environmental and health issues in republic of korea. due to lack of epidemiological studies and insufficient public awareness about radon, effective parameter ranking system is required to establish protocols for future field sampling and settlement construction. this research propose the irc parameter ranking system based on field measure...

Ranking of alternatives is a common, difficult and repeatedly addressed problem, especially when it requires negotiation of experts. The celebrated Arrow’s impossibility theorem expresses formally its difficulty. In spite of theprogressmadebyadopting soft ranking, the problem is far from being generically solved. The paper provides a, probably novel, problem formulation by viewing ranking of al...

We propose a novel approach to generating a ranking of items in a network (e.g., of web pages connected by links or of articles connected by citations). We transform the network into an exchange economy, and use the resulting competitive equilibrium prices of the network nodes as their ranking. The widely used Google's PageRank comes as a special case when the nodes are represented by Cobb-Doug...

Data management systems, like database, information extraction, information retrieval or learning systems, store, organize, index, retrieve and rank information units, such as tuples, objects, documents, items to match a pattern (e.g. classes and profiles) or meet a requirement (e.g., relevance, usefulness and utility). To this end, these systems rank information units by probability to decide ...

The paper describes a system for end-user development using natural language. Our approach uses a ranking model to identify the actions to be executed followed by reference and parameter matching models to select parameter values that should be set for the given commands. We discuss the results of evaluation and possible improvements for future work.

Ranking algorithms are often introduced with the aim of automatically personalising search results. However, most ranking algorithms developed in the machine learning community rely on a careful choice of some regularisation parameter. Building upon work on the regularisation path for kernel methods, we propose a parameter selection algorithm for ranking SVM. Empirical results are promising.

Image ranking is a task that involves different parameters. They depend on the intrinsic characteristics of an image, but also on the indexing language used for representing its semantic content. We developed a weighting model that combines these parameters in a general scheme. Finding the best balance between the parameters is not straightforward. Different parameter combinations leads to diff...