This paper tackles problems encountered in mining of incomplete data for knowledge discovery of construction databases. As historical construction data are expensive to collect, any waste of incomplete data means not only loss of knowledge but also increase of costs for knowledge discovery of construction engineering. Unfortunately, incompleteness is commonplace in the existing construction dat...

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. In this chapter we discuss how fuzzy logic extends the envelop of the main data mining tasks: clustering, classification, regression and association rules. We begin by presenting a formulation of the data mining using fuzzy logic attributes. Then, for each task, we pro...

Effective methods for feature and model structure selection are very important for data-driven modeling, data mining, and system identification tasks. This paper presents a new method for selecting important variables (regressors) in nonlinear (dynamic) models with mixed discrete (categorical, fuzzy) and continuous inputs and outputs. The proposed method applies fuzzy association rule mining. T...

Fuzzy spatial data mining technique has been developed to extract relationships describing relative positions of classes of objects from raster images. Demand has been increased for complex data in various applications. These complex data can be easily represented and manipulated by Object-oriented systems it is also capable of managing complicated and uncertain relationship existing among them...

From the definition of fuzzy sets by Zadeh in 1965, fuzzy logic has become a significant area of interest for researchers on artificial intelligence. In particular, Professor Mamdani was the pioneer who investigated the use of fuzzy logic for interpreting the human derived control rules, and therefore his work was considered a milestone application of this theory. In this work, we aim to carry ...

In this paper, we present the discovery of rules for different challenges encountered in video indexing. These rules should be considered as knowledge that can be used as a guideline for the development of better indexing tools. We use a fuzzy decision tree to extract the rules based on color proportions of key-frames extracted from one single video-news. Experimental results and comparisons wi...

Motivated by the increased need for formalized representations of the field of Data Mining and the successfull results of using Formal Concept Analysis (FCA) and Ontology, we introduce in this paper our contribution in order to support flexible query in large Database using FCA and Fuzzy Ontology. We first present our new approach for automatic generation of Fuzzy Ontology of Data Mining (FODM)...

Many methods have been proposed for mining fuzzy sequential patterns. However, most of conventional methods only consider the occurrences of fuzzy itemsets in sequences. The fuzzy sequential patterns discovered by these methods are called as positive fuzzy sequential patterns. In practice, the absences of frequent fuzzy itemsets in sequences may imply significant information. We call a fuzzy se...

Data mining is a technique for discovering hidden knowledge of strategic importance from large databases. This technique is currently being successfully used by a number of real-world applications. Data mining is a tool for increasing the productivity of people trying to build predictive models. Both disciplines have been working on problems of pattern recognition and classification. Rule induc...

This paper proposes a framework for mining market basket data to generate Nutritional Patterns (NPs) and a method for analysing generated nutritional patterns using Fuzzy Association Rule Mining. Edible attributes are filtered from transactional input data by projections and are then converted to Required Daily Allowance (RDA) numeric values. The RDA database is...