This paper describes the BiomedTK software framework, created to perform massive explorations of machine learning classifiers configurations for biomedical data analysis over distributed Grid computing resources. BiomedTK integrates ROC analysis throughout the complete classifier construction process and enables explorations of large parameter sweeps for training third party classifiers such as artificial neura...
Many data sets derived from the web are large, high-dimensional, sparse and have a Zipfian distribution of both classes and features. On such data sets, current scalable clustering methods such as streaming clustering suffer from fragmentation, where large classes are incorrectly divided into many smaller clusters, and computational efficiency drops significantly. We present a new clustering algorithm based on ...
In this paper we explore the potential benefits of concepts such as visual interactive modelling and simulation to devise and implement a coopera-tive network editor embedded in a collaborative environment for transport analysis. Traditional approaches lack adequate means to foster integrated analy-ses of transport systems either because they are strict in terms of purpose or be-cause they do not allow multiple...
The Airline Operations Control Centre (AOCC) tries to solve unexpected problems that might occur during the airline operation. Problems related to aircrafts, crewmembers and passengers are common and the actions towards the solution of these problems are usually known as operations recovery. Usually, the AOCC tries to minimize the operational costs while satisfying all the required rules. In this paper we prese...
The Airline Operations Control Center (AOCC) tries to solve unexpected problems that might occur during the airline operation. Problems related to aircrafts, crewmembers and passengers are common and the actions towards the solution of these problems are usually known as operations recovery. In this paper we present the implementation of a Distributed Multi-Agent System (MAS) representing the existing roles in ...
We present a multi-pass clustering approach to large scale, wide-scope named-entity disambiguation (NED) on collections of web pages. Our approach uses name co-occurrence information to cluster and hence disambiguate entities, and is designed to handle NED on the entire web. We show that on web collections, NED becomes increasingly difficult as the corpus size increases, not only because of the challenge of sca...
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