Ermir Rogova

On imprecision intuitionistic fuzzy sets & OLAP - the case for KNOLAP

Traditional data repositories are typically focused on the storage and querying of crisp-precise domains of data. As a result, current commercial data repositories have no facilities for either storing or querying imprecise-approximate data. However, when considering scientific data (i.e. medical data, sensor data etc) value uncertainty is inherited to scientific measurements. In this paper we revise the context of “value uncertainty”, and examine common models related to value uncertainty as part of the OLAP model. We present our approach for extending the OLAP model to include treatment of value uncertainty as part of a multidimensional model inhabited by flexible date and non-rigid hierarchical structures of organisation.

The notion of H-IFS: An approach for enhancing the OLAP capabilities in oracle10g

Query answering requirements for a knowledge‐based treatment of user requests led us to introduce the concept of closure of an intuitionistic fuzzy set over a universe that has a hierarchical structure. We recommend the automatic analysis of queries according to concepts defined as part of knowledge‐based hierarchies to guide the query answering as part of an integrated database environment with the aid of hierarchical intuitionistic fuzzy sets (H‐IFS). In this paper based on the notion of H‐IFS, we propose an ad hoc utility build on top of Oracle10g that allows us to enhance the query capabilities of by providing better, knowledgeable, and optimized answers to users requests.

Expressing hierarchical preferences in OLAP queries

OLAP query answering requirements for a knowledge based treatment of user requests led us to introduce the concept of hierarchical preferences over a universe that has a hierarchical structure. We introduce the automatic analysis of queries according to concepts defined as part of knowledge based hierarchy in order to guide the query answering as part of a data-warehouse environment with the aid of hierarchical Intuitionistic fuzzy sets, H-IFS. Based on the notion of H-IFS we propose an ad-hoc utility build on top of current OLAP tools like Oracle10g that allows us to enhance the query capabilities of by providing better and knowledgeable answers to user’s requests. The theoretical aspects as well the practical issues and achieved results are presented throughout the rest of the paper.

The notion of H-IFS in data modelling

In this paper we revise the context of ldquovalue imprecisionrdquo, as part of an knowledge-based environment. We present our approach for including value imprecision as part of a non-rigid hierarchical structures of organization. This led us to introduce the concept of closure of an intuitionistic fuzzy set over a universe that has a hierarchical structure. Intuitively, in the closure of this intuitionistic fuzzy set, the ldquokind ofrdquo relation is taken into account by propagating the degree associated with an element to its sub-elements in the hierarchy. We introduce the automatic analysis according to concepts defined as part of a knowledge hierarchy in order to guide the query answering as part of an integrated database environment with the aid of hierarchical intuitionistic fuzzy sets.

The notion of H-IFS -an approach for enhancing query capabilities in Oracle10g

Query answering requirements for a knowledge based treatment of user requests led us to introduce the concept of closure of an Intuitionistic fuzzy set over a universe that has a hierarchical structure. We introduce the automatic analysis of queries according to concepts defined as part of a knowledge based hierarchy in order to guide the query answering as part of an integrated database environment with the aid of hierarchical Intuitionistic fuzzy sets, H-IFS. In this paper based on the notion of H-IFS we propose an ad-hoc utility build on top of Oracle10g that allows us to enhance the query capabilities of by providing better and knowledgeable answers to userpsilas requests. The theoretical aspects as well the practical issues and achieved results are presented throughout the rest of the paper.

Representation of Value Imperfection with the Aid of Background Knowledge: H-IFS

An Integrated Data Management System is required for representing and managing indicative information from multiple sources describing the state of an enterprise. In such environments, information may be partially known because the related information from the real world corresponds to a set of possible values including the unknown. Here, we present a way to replace unknown values using background knowledge of data that is often available arising from a concept hierarchy, as integrity constraints, from database integration, or from knowledge possessed by domain experts. We present and examine the case of H-IFS to represent support contained in subsets of the domain as a candidate for replacing unknown values mostly referred in the literature as NULL values.