Abstract Machine learning algorithms are often faced with several data related problems.
Real-world datasets come in various types and dimensions, each of which constitute some …

Abstract In this chapter Multi-Objective Evolutionary Algorithms (MOEAs) are introduced and
some details discussed. A presentation of some of the concepts in which this type of …

Decision tree is a well known approach for classification in data mining. C4. 5 and
Classification and Regression Trees (CART) are two widely used decision tree algorithms …

In a time of growing complexity and amount of a product related data, ontology has show to
be an efficient and convenient method for structuring and modeling the domain of interest. It …

This dissertation proposes a novel methodology for knowledge discovery in large data sets,
with a focus on unstructured and semi-structured textual data. To our knowledge, extracting …

The impact and popularity of competition concept has been increasing in the last decades
and this concept has escalated the importance of giving right decision for organizations …

In this paper, an intelligent model for analyzing and predicting cloud computing resource
utilization is proposed to enhance on-demand services in cloud computing systems. The …

This project results report introduces a work project in which a prototype was built as a “proof
of concept” for a data analysis tool that automates data preparation, exploration and …

Data Mining techniques plays a vital role like extraction of required knowledge, finding
useful information to make strategic decision in a novel way which in term understandable …

Data mining is the process of analyzing data from different perspectives and summarizing it
into useful information. It is the process of fetching hidden knowledge from a wide store of …