The advancement in technology, competitive market environment and changing behaviour of customers has generated an increased interest in direct marketing method for marketing. Data mining technology can predict and detect the changes in customer behaviour which facilities the effective planning of direct marketing campaigns. The objective of this paper is to generate a simplified data mining fr...

This paper is a literature review of a new algorithm for mining association rules in a spatial database. Spatial data mining, or knowledge discovery in large spatial databases, is the process of extracting implicit knowledge, spatial relations, or other patterns not explicitly stored in spatial databases. Recently, there has been a lot of research in data mining and these studies led to a set o...

Data mining techniques are largely used in different sectors of the economy and they increasingly are playing an important role in agriculture and environment-related areas. This paper aims to show our vision on the importance of knowing and efficiently using data mining and machine learning-related techniques for knowledge discovery in the field of agriculture and environment. Efforts for sear...

In this paper we describe a knowledge-based system for extracting knowledge from academic and registrar databases using source mining, where the sources are data or text. Other sources not included in this research are image, sound or gestures. Patterns of student behaviour were obtained by examining data from student attributes such as city of birth, scholarship needs, field of knowledge and m...

Data mining refers to the technique of obtaining hidden, previously unknown and possibly significant knowledge from humongous amount of data. Data mining uses a combination of a vast knowledge base, advanced analytical skills, and domain knowledge to unveil hidden trends and patterns which can be applied in almost any sector ranging from business to medicine, then to Engineering. Nonetheless ed...

the success or failure of an organization has a direct relationship with how its human resources are employed and retained. it is the case that organizations keep large amounts of information and data on entrance evaluations and processes. this information, however, is often left unutilized. data mining is considered a solution for analyzing these data. this paper is investigating educated and ...

ata Mining is a discovery of knowledge used basically used for finding or exploring the new facts among datasets. It allows the user to find the hidden data among available datasets. Data mining consists of various components including clustering, classification, association rules, sequence analysis etc. Unlabeled data are becoming common and mining such databases becomes more challenging. Clus...

Business process management and business intelligence are fields which gain a lot of attention in recent years. These techniques try to improve not only efficiency of processes but also save considerable cost. Graph based representation of concepts (objects, data) are also used in business domain to support aforementioned techniques. Graph mining methods are successful in many fields for discov...

Knowledge Discovery in Databases (KDD) is the process of automatically searching patterns from large volumes of data by using specific data mining techniques. Classification, association, and associative classification (integration of classification and association) rule mining are popularly used rule mining techniques in KDD for harvesting knowledge in the form of rule. The classical rule mini...

Data mining techniques are largely used in different sectors of the economy and they increasingly are playing an important role in agriculture and environment-related areas. This paper aims to show our vision on the importance of knowing and efficiently using data mining and machine learning-related techniques for knowledge discovery in the field of agriculture and environment. Efforts for sear...