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We hypothesised that biomass smoke exposure is associated with an airway-predominant chronic obstructive pulmonary disease (COPD) phenotype, while tobacco-related COPD is associated with an emphysema-predominant phenotype. In this cross-sectional study, female never-smokers with COPD and biomass exposure (n=21) and female ex-cigarette smokers with COPD(More)
Web usage mining has recently attracted attention as a viable framework for extracting useful access pattern information, such as user profiles, from massive amounts of Web log data for the purpose of Web site personalization and organization. These efforts have relied mainly on clustering or association rule discovery as the enabling data mining(More)
BACKGROUND Delirium is an important problem especially in older medical inpatients. OBJECTIVE The authors asked whether delirium and its duration are associated with higher mortality in a 3-month follow-up period. METHOD In this prospective cohort study, inpatients age 65 and older were assessed every 48 hours with the Confusion Assessment Method. (More)
Artificial Immune System (AIS) models offer a promising approach to data analysis and pattern recognition. However, in order to achieve a desired learning capability (for example detecting all clusters in a dat set), current models require the storage and manipulation of a large network of B Cells (with a number often exceeding the number of data points in(More)
The expanding and dynamic nature of the Web poses enormous challenges to most data mining techniques that try to extract patterns from Web data, such as Web usage and Web content. While scalable data mining methods are expected to cope with the size challenge, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary(More)
In this paper, we study the behavior of collaborative filtering based recommendations under evolving user profile scenarios. We propose a systematic validation methodology that allows for simulating various controlled user profile evolution scenarios and validating the studied recommendation strategies. Through the presented work, we observe the effect of(More)
Data mining has recently attracted attention as a set of efficient techniques that can discover patterns from huge data. More recent advancements in collecting massive evolving data streams created a crucial need for dynamic data mining. In this paper, we present a genetic algorithm based on a new representation mechanism that allows several phenotypes to(More)
In addition to its ever-expanding size and lack of structure, the World Wide Web has not been responsive to user preferences and interests. Personalization deals with tailoring a user's interaction with the Web information space based on information about him/her. Mass profiling is based on general trends of usage patterns (thus protecting privacy) compiled(More)
While scalable data mining methods are expected to cope with massive Web data, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary stoppages and reconfigurations is still an open challenge. This dynamic and single pass setting can be cast within the framework of mining evolving data streams. In this paper, we(More)