A Data Warehouse (DW) is a repository of information collected from multiple sources, stored under a unified schema, and that usually resides at a single site. DWs are constructed via a process of data cleaning, data integration, data transformation, data loading, and periodic data refreshing. Integration of data sources refers to the task of developing a common schema as well as data transform...

supply chain management is one of modern approach in the field of operation and production management. nowadays success and survival of manufacturing organizations depend on effectiveness and productivity of supply chains. this research tries to investigate contributing factor to enhance supply chain productivity. then by using fuzzy promethe-a multiple attribute decision making (madm) - tous a...

this paper proposes a method for ranking decision making units (dmus) using some of the multiple criteria decision making / multiple attribute decision making          (mcdm /madm) techniques, namely, interval analytic hierarchy process (iahp)          and the technique for order preference by similarity to an ideal solution (topsis).          since the efficiency score of unity is assigned to ...

Attribute reduction with fuzzy rough set is an effective technique for selecting most informative attributes from a given realvalued dataset. However, existing algorithms for attribute reduction with fuzzy rough set have to re-compute a reduct from dynamic data with sample arriving where one sample or multiple samples arrive successively. This is clearly uneconomical from a computational point ...

In this paper, we examine Decision Graphs, a generalization of decision trees. We present an inference scheme to construct decision graphs using the Minimum Message Length Principle. Empirical tests demonstrate that this scheme compares favourably with other decision tree inference schemes. This work provides a metric for comparing the relative merit of the decision tree and decision graph form...

Data Mining is a process related to analysis, understanding and knowledge extraction from databases. In order to perform this process it is usually necessary to represent the data in the so called attribute-value format. This work proposes an extension of a methodology which supports, through a semi-automatic process, the construction of a table in the attribute-value format from information co...

How to process missing attribute values is an important data preprocessing problem in data mining and knowledge discovery tasks. A commonly-used and naive solution to process data with missing attribute values is to ignore the instances which contain missing attribute values. This method may neglect important information within the data and a significant amount of data could be easily discarded...