Clustering categorical data poses two challenges defining an inherently meaningful similarity measure, and effectively dealing with clusters which are often embedded in different subspaces. In this paper, we propose a novel divisive hierarchical clustering algorithm for categorical data, named DHCC. We view the task of clustering categorical data from an optimization perspective, and propose effective procedures to initialize and refine the splitting of clusters. The initialization of the splitting is based on multiple correspondence analysis (MCA). We also devise a strategy for deciding when to terminate the splitting process. The proposed algorithm has five merits. First, due to its hierarchical nature, our algorithm yields a dendrogram representing nested groupings of patterns and similarity levels at different granularities.
Dementia causes cognitive deficits producing functional impairments. Continuous care and monitoring are thus compulsory to keep at home elders suffering from dementia. Intelligent habitat can play a central role toward a global and integrated solution and alleviate relatives from the care burden. The general idea is twofold. On the one hand, the physical environment could supplement elder cognitive impairments by providing personalized environmental cues that assist him in achieving his tasks. On the other hand, the intelligent house could maintain a link with relatives and medical care system to inform them of the evolution of the disease and to alert them in case of emergency. This paper shows how intelligent houses can deliver such cognitive assistance to elders, prolonging the time they can remain at home. First we derive the requirements for cognitive assistance by an intelligent habitat from the impact of the Alzheimer disease in the daily living of elders. Subsequently we describe the layered computer infrastructure needed to implement a distributed intelligent house information system. The implementation of such a pervasive system raises many issues that are not trivial from a computer science perspective. In this paper, we focus on modelling issues. Finally a simple scenario is used to exemplify the interactions between the intelligent house and the elders.
Miace as a human cognitive architecture is a computational model that explains how a student acquires, encodes and uses domain knowledge. Because Miace takes into account the cognitive psychological laws and the environment in which the student works, it can be used as a virtual student in help systems dedicated to pedagogical formation, in intelligent tutoring systems, in cooperative learning applications and for the conception of didactic material. This paper describes the implementation of Miace and discusses the Miace theoretical components from three point of view: temporal, their roles in cognitive activity and their generic or functional forms. A comparison is done to show the originality and the contribution of Miace in user modeling.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.