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Nowadays data sets are available in very complex and heterogeneous ways. The mining of such data collections is essential to support many real-world applications ranging from healthcare to marketing. In this work, we focus on the analysis of " complex " sequential data by means of interesting sequential patterns. We approach the problem using an elegant(More)
INTRODUCTION Metformin-associated lactic acidosis (MALA) is a classic side effect of metformin and is known to be a severe disease with a high mortality rate. The treatment of MALA with dialysis is controversial and is the subject of many case reports in the literature. We aimed to assess the prevalence of MALA in a 16-bed, university-affiliated, intensive(More)
In this paper, we presents a research work based on formal concept analysis and interest measures associated with formal concepts. This work focuses on the ability of concept lattices to discover and represent special groups of individuals, called social communities. Concept lattices are very useful for the task of knowledge discovery in databases, but they(More)
In this paper, we are interested in the analysis of sequential data and we propose an original framework based on FCA. For that, we introduce sequential pattern structures, an original specification of pattern structures for dealing with sequential data. Sequential pattern structures are given by a subsumption operation between set of sequences, based on(More)
The Internet has totally changed the way information is published and shared in medicine. With web 2.0 and semantic web technologies, web applications allow now collaborative information editing in a way that can be reused by machines. These new tools could be used to in local health networks to promote the editing and sharing of medical knowledge between(More)
BACKGROUND Socioeconomic deprivation is not easily measurable in hospital information systems. However, its identification is essential, as it is associated with morbidity and hospital length of stay (LOS). We aimed at studying the feasibility of using routinely recorded individual and area-based socioeconomic indicators, and assessing their relation with(More)
This paper presents a research work in the domains of sequential pattern mining and formal concept analysis. Using a combined method, we show how concept lattices and interestingness measures such as stability can improve the task of discovering knowledge in symbolic sequential data. We give example of a real medical application to illustrate how this(More)
This paper presents an original experiment based on frequent itemset search and lattice based classification. This work focuses on the ability of iceberg-lattices to discover and represent flows of patient within a healthcare network. We give examples of analysis of real medical data showing how Formal Concept Analysis techniques can be helpful in the(More)
Sequential pattern mining is an approach to extract correlations among temporal data. Many different methods were proposed to either enumerate sequences of set valued data (i.e., itemsets) or sequences containing multidimensional items. However, in many real-world scenarios , data sequences are described as events of both multi-dimensional and set valued(More)
Learning Analytics by nature relies on computational information processing activities intended to extract from raw data some interesting aspects that can be used to obtain insights into the behaviours of learners, the design of learning experiences, etc. There is a large variety of computational techniques that can be employed, all with interesting(More)