Data mining Essays

  • Mining In Data Mining

    781 Words  | 4 Pages

    Large amounts of data are being generated and stored every day in Organizational computer database systems. Data mining is to discover knowledge from large amounts of data and is widely used in business world. Mining association rules from transactional data is becoming a popular and important knowledge discovery technique. Association rule mining is a data mining task that discovers relationships among items in a transactional database. One of the branches of data mining is Associative Classification

  • Data Mining Lab Report

    3531 Words  | 15 Pages

    relevant to the particular text mining problem. Then perform text documents clustering based on Genetic Algorithm (GA) with mutation rate. The mutation operation is important to the achievement of GA since it enlarges the text documents search guidelines and

  • Importance Of Data Mining

    990 Words  | 4 Pages

    DATA MINING IN INSTITUTIONAL DEDUCTION DATA MINING: Data mining is a process of analyzing data from different perspectives and summarizing it into useful information. Data are any facts, numbers, text that can be processed by a computer. The patterns, associations, or relationships among all collected data can provide information. Information can be converted into knowledge about historical patterns and future trends. To maximize user access and

  • Advantages And Disadvantages Of Data Mining

    1498 Words  | 6 Pages

    advances in data collection and storage technology have enabled organizations to accumulate vast amount of data. Simple transactions of everyday life such as using a cash card, credit card, a telephone monitoring system or browsing the web lead to automated data storage. In many cases, these large volumes of data can be mined for interesting and relevant information in a wide types of applications. When the quantity of the underlying data is huge, it tends to a number of computational and mining challenges

  • Disadvantages In Data Mining

    2171 Words  | 9 Pages

    IN DATA MINING 3.1 INTRODUCTION TO DATAMINING The increasing computerization with in the world around us has meant that the existence of database containing vast quantities of data is now a fact of everyday life. The enormous quantities of data which are now stored in databases create a problem in that it becomes very difficult to make meaningful sense of such a large quantity of data. For human investigators, the process of extracting meaningful information from such a large amount of data becomes

  • Pros And Cons Of Data Mining

    5709 Words  | 23 Pages

    Data mining can be viewed as a result of the normal development of information technology Since 1960, database and information technology has been growing methodically from primitive file processing systems to complicated and prevailing database systems [11] [13]. Figure 1.1: History of data base system and data mining Data mining drives its name for searching a important information from a large database to utilize this information in better way. It is, though, a misnomer, as mining for gold

  • Outliers In Data Mining

    784 Words  | 4 Pages

    Abstract- Outlier detection is an active area for research in data set mining community. Finding outliers from a collection of patterns is a very well-known problem in data mining. Outlier Detection as a branch of data mining has many applications in data stream analysis and requires more attention. An outlier is a pattern which is dissimilar with respect to the rest of the patterns in the data set. Detecting outliers and analyzing large data sets can lead to discovery of unexpected knowledge in area

  • Outlier In Data Mining

    1811 Words  | 8 Pages

    1.1 Introduction Today in Dataset there exist data objects that do not comply with the general behavior or model of the data. Such data objects which are heavy different from or inconsistent with the remaining set of data, are called outliers. An outlier is a data set which is different from the remaining data. Outlier is also denoted to as deformity, deviants or anomalies in the data mining and statistics literature. In most applications the data is produced by one or more generating processes

  • Text Mining Techniques In Data Mining

    2514 Words  | 11 Pages

    Abstract Data Mining is the process to extract hidden predictive information from database and transform it into understandable structure for future use. The assorted domains in data mining are Web Mining, Text Mining, Sequence Mining, Graph Mining, Temporal Data Mining, Spatial Data Mining (SDM), Distributed Data Mining (DDM) and Multimedia Mining. Some of the applications of data mining, it is used for financial data analysis, retail and telecommunication industries, science and engineering and

  • The Pros And Cons Of Data Mining

    710 Words  | 3 Pages

    discovery also known as data mining is the processes involve penetration into tremendous amount of data with the support from computer and web technology for examining the data. Data mining is a process of discovering interesting knowledge by extracting or mining the data fromlarge amount of data and the process of finding correlations or patterns among dozens of fields in large relational databases [3, 4]. Privacy Preserving in Data Publishing (PPDP) is very important in data mining when publishing individual

  • Outlier Detection In Data Mining

    2241 Words  | 9 Pages

    Data mining is a system that brings up the light to hidden and valuable information from the data and the facts revealed by data mining which were previously not known, theoretically useful, and of high quality. Data mining offers a means by which we can explores the knowledge in database. Data stream mining and finding outliers are dynamic research areas of data mining. Outlier detection is a division of data mining and has many applications in data stream analysis. This requires consideration from

  • Data Mining Case Study

    1269 Words  | 6 Pages

    1.1. DATA MINING Data mining refers to extracting or mining knowledge from large amounts of data. Data mining has attracted a great deal of attention in the information industry and in society as a whole in recent years, due to the wide availability of huge amounts of data and the forthcoming need for turning such data into useful information and knowledge. The information and knowledge gained can be used for applications ranging from market analysis, fraud detection, and customer retention, to

  • Privacy Issues In Data Mining

    954 Words  | 4 Pages

    Data mining is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data preprocessing, model and inference considerations, interestingness

  • Examples Of Negative Data Mining

    2396 Words  | 10 Pages

    ASSOCIATION RULE MINING L. Ravi kiran Goud Dr. Y. Rama Devi SECOND YEAR MTECH CSE Head of the CSE Dept CBIT HYDERABAD CBIT HYDERABAD ABSTRACT Data mining is a technique of extracting knowledge

  • Importance Of Data Mining In Telecommunication

    1333 Words  | 6 Pages

    DATA MINING IN TELECOMMUNICATION NIKHILA.C.P, KRISHNENDU.N.S, LIDIYA MARY ANTONY, DEPARTMENT OF COMPUTER SCIENCE ST JOSEPH’S COLLEGE IRINJALAKUDA ABSTACT Data mining is a process of extracting information from large amount of data and transform it into an understandable structure for further use. Telecommunication companies generate a great amount of data including call details, describing the calls that traverse the telecommunication networks, network data, describing the

  • A Short Summary: Big Data Vs. Data Mining

    1007 Words  | 5 Pages

    Big Data vs Data Mining 1. Introduction What is Big Data? Big Data refers to huge volume of data that can be structured, semi-structured and unstructured. It comprises of 5 Vs i.e. a. Volume: It refers to amount of data or size of data that can be in quintillion when comes to big data. b. Variety: It refers to different types of data like social media, web server logs etc. c. Velocity: It refers to how fast data is growing, data is exponentially growing and at a very fast rate. d. Veracity: It

  • Case Study: Spyware Detection Using Data Mining

    1660 Words  | 7 Pages

    Spyware Detection Using Data Mining Prof. Mahendra Patil Atharva College Of Engineering Head Of Department(CS) 2nd line of address onlymahendra7@yahoo.com Karishma A. Pandey Atharva College Of Engineering 1st line of address 2nd line of address pandeykarishma5@gmail.com Madhura Naik Atharva College Of Engineering 1st line of address 2nd line of address madhura264@gmail.com Junaid Qamar Atharva College Of Engineering 1st line of address 2nd line of address junaiddgreat@gmail.com

  • Data Mining Literature Review

    1026 Words  | 5 Pages

    REVIEW ON DATA MINING Poornima D Jiawei Han Micheline Kamber Abstract: My main research involved how Data Mining process involves in real world and the reach of data mining and utilities of data mining. Data Mining has a great deal of attention due to wide availability of huge amounts of data, where these imminent need for turning such data into a useful information and knowledge. From the last development of data collection and database creation mechanisms served as prerequisite from development

  • Two Data Mining Methodologies

    2168 Words  | 9 Pages

    Assignment a. Discuss the two data mining methodologies The process of going through massive sets of data looking out for unsuspected patterns which can provide us with advantageous information is known as data mining. With data mining, it is more than possible or helping us predict future events or even group populations of people into similar characteristics. Cross Industry Standard Process for Data Mining (CRISP-DM) is a 6-phase model of the entire data mining process which is commonly used

  • Big Data Mining Case Study

    1723 Words  | 7 Pages

    CHALLENGES WITH BIG DATA MINING: A SURVAY Libina Rose Sebastian Dept. of Computer Science and Engineering St. Joseph College of Engineering and Technology Palai, Kerala, India libina.libu@gmail.com Mereen Thomas Dept. of Computer Science and Engineering St. Joseph College of Engineering and Technology Palai, Kerala, India mereen.thomas@gmail.com Abstract— Big data is a collection of dataset which are so large and complex. Data sets are growing day by day and sharing, transfer, capture, storage