Entity Attribute Value (EAV) storage model is extensively used to manage healthcare data in existing systems, however it lacks search efficiency. This study examines an entity attribute value style modeling approach for standardized Electronic Health Records (EHRs) database. It sustains qualities of EAV (i.e., handling sparseness and frequent schema evolution) and provides better performance fo...

We consider the problem of aggregation for uncertain and imprecise data. For such data, we define aggregation operators and use them to provide information on properties and patterns of data attributes. The aggregates that we define use the Kullback-Leibler information divergence between the aggregated probability distribution and the individual tuple data values. We are thus able to provide a ...

Abstract: Aimed at the situation that the plan attribute value is a three-parameter interval grey number and that attribute weight is uncertain, a three-parameter interval grey number multi-attribute decision making method based on information entropy is proposed. In this study, we combine the three-parameter interval grey number decision-making problem with information entropy, build the dista...

Finding all closed frequent itemsets is a key step of association rule mining since the non-redundant association rule can be inferred from all the closed frequent itemsets. In this paper we present a new method for finding closed frequent itemsets based on attribute value lattice. In the new method, we argue that vertical data representation and attribute value lattice can find all closed freq...

In this paper, we present a model-driven distributed information management system called MDIM that can resolve multi-attribute range queries about large-scale networked systems. Different from previous work, MDIM can adaptively configure its information collection and query resolution operations based on a dynamically maintained information model. The information model captures both statistica...

We introduce the concept of object functional dependency for object oriented models, and we study consistency, satisfaction and functional implication in the context of a class extension. We then use functional implication to deene the formal semantics of a class extension by a least xpoint construction. The concepts introduced here are motivated by similar and well known concepts of the relati...

Object-relational mapping (mapping object-oriented software systems to relational databases) remains a challenging undertaking because of the inherent differences between these two technologies. Effective application of this technique in biomedical informatics applications can provide robust, adaptive solutions but requires careful attention to specific issues in the bioscience domain. Mapping ...

In this paper, we discuss a multiperiod portfolio selection problem with fuzzy returns. We present a new credibilitic multiperiod mean semi- absolute deviation portfolio selection with some real factors including transaction costs, borrowing constraints, entropy constraints, threshold constraints and risk control. In the proposed model, we quantify the investment return and risk associated with...