CHAPTER 1 INTRODUCTION The explosive growth in the amount of data and the challenges for finding interesting patterns from huge amount of data lead to emergence of data mining. Data mining is the process of extracting the interesting (valid, novel, useful and understandable) patterns from the huge data that are actionable and may be used for enterprise’s decision making process. Data mining is one of the core processes of knowledge discovery in databases. The basic types of data mining techniques are association rules, classification and clustering, web mining and sequential pattern mining. Association rule mining is one of the basic and most important data mining techniques. It extracts the interesting correlations, frequent patterns, associations among the item sets that may be used in decision making process. For example in case of grocery store, the association rules can be set of items that are brought together by the customer. For example “30% of the people who buy noodles also buy tomato ketchup”. This pattern can be helpful for developing marketing strategies and advertisement plan. Association rules can be helpful in areas such as market and risk management, customer segmentation, finance, telecommunication networks, intrusion detection, web usage mining and bioinformatics. Today, business enterprises store large amount of data from their daily operations such data is mainly transaction database. Finding all interesting association rule from large database is quite challenging. The most of the current approaches require multiple database scans and are very expensive. The goal is to build efficient approach that require lesser space and has lesser computation overheads. . CHAPTER 2 PROBLEM STATEMENT Consi... ... middle of paper ... ...date itemsets that does not expects to be large, thus avoiding unnecessary effort to count these itemsets. The AIS algorithm requires more and takes more effort for candidate set generation which are further reduced. Along with this main drawback, also over the database it requires too many passes. 3.1.2 Apriori Algorithm: Apriori algorithm was given which was improved AIS by Agrawal et al[2]. FP- growth algorithm initially scans the transaction database to get the frequencies of the items (or the support of the single item). The items whose frequency is less than the given minimum support are discarded from the transactions. Also in each transaction, the items are sorted in descending order according to their frequency in the database. The descending order leads to the shorter execution time rather than ascending or random order.
Here, the number of rows of Applicaion definition is set to 1 since we are using a single application i.e. FTP. The name of application is given as FTP_Application. In the description of FTP inter request time, the time taken to transfer the file, is set to constant (3600) and the File size is set to constant (10000000) which is 10MB.
The K-Means algorithm is used for cluster analysis by dividing data points into k clusters. The K means algorithm will group the data into the cluster based on feature similarity.
Classification Text documents are arranged into groups of pre-labeled class. Learning schemes learn through training text documents and efficiency of these system is tested by using test text documents. Common algorithms include decision tree learning, naive Bayesian classification, nearest neighbor and neural network. This is called supervised learning.
McGonigle and Mastrian (2013) defines data mining as a process of utilizing software to sort through data so as to discover patterns and ascertain or establish relationships. They also state this process may help to discover or uncover previously unidentified relationships among the data in a database. Data mining is very important to healthcare organizations. It can help in ways such as to determine treatment effectiveness, identify problems, decrease costs for the organization, and can even detect possible fraudulent activity. Not only is data mining used in healthcare, but it is also used in other businesses as well. Although data mining is a great asset to healthcare, an informatics nurse has to be very careful due to the lack of a standardized
Big Data is a term used to refer to extremely large and complex data sets that have grown beyond the ability to manage and analyse them with traditional data processing tools. However, Big Data contains a lot of valuable information which if extracted successfully, it will help a lot for business, scientific research, to predict the upcoming epidemic and even determining traffic conditions in real time. Therefore, these data must be collected, organized, storage, search, sharing in a different way than usual. In this article, invite you and learn about Big Data, methods people use to exploit it and how it helps our life.
Data mining has emerged as an important method to discover useful information, hidden patterns or rules from different types of datasets. Association rule mining is one of the dominating data mining technologies. Association rule mining is a process for finding associations or relations between data items or attributes in large datasets. Association rule is one of the most popular techniques and an important research issue in the area of data mining and knowledge discovery for many different purposes such as data analysis, decision support, patterns or correlations discovery on different types of datasets. Association rule mining has been proven to be a successful technique for extracting useful information from large datasets. Various algorithms or models were developed many of which have been applied in various application domains that include telecommunication networks, market analysis, risk management, inventory control and many others
There is a debate between the benefits and potential informational privacy issues in web-data mining. There are large amount of valuable data on the web, and those data can be retrieved easily by using search engine. When web-data mining techniques are applied on these data, we can get a large number of benefits. Web-data mining techniques are appealing to business companies for several reasons [1]. For example, if a company wants to expand its bu...
In the beginning, businesses used information technology for automating the processes primarily to reduce labor costs. Subsequently, information technology is used for delivering information with speed and accuracy.
With just a few clicks, any range of dates can be defined from which statistics can be viewed as well as navigation from general data to a more specific data and everything from bounce rates to conversion rates. This is one of the biggest advantages provided by Google Analytics...
6- Developing of new tools, for all the new fields of studying, and developing programs for data mining and analysis of huge databases.
HAND, D. J., MANNILA, H., & SMYTH, P. (2001).Principles of data mining. Cambridge, Mass, MIT Press.
Big data is a concept that has been misunderstood therefore I will be writing this paper with the intentions of thoroughly discussing this technological concept and all its dimensions with regard to what constitutes big data and how the term came about. The rapid innovations in Information Technology have brought about the realisation of big data. The concept of big data is complex and has different connotations but I intend to clarify its functions. Big data refers to the concept of a collection of large and complex amounts of data that are found extremely difficult to notate or even process by most on-hand devices and database technologies.
The dynamics of our society bring many challenges and opportunities to the business world. Within the last decade, hundreds of jobs have emerged particularly in the technology sector to help keep up with the ever-changing world and to compete on a larger and better scale than the competition. Two key job markets and the basis of this research paper are business intelligence or BI and data mining or DM. These two fields play a very important role in small to large companies and are becoming higher desired sectors within the back offices of the workplace. This paper will explore what the meaning of BI and DM really is, how they are used and what we can expect as workers and learners of the technology and business fields for the future.
Data mining, or knowledge discovery, is the computer-driven process of searching through and analysing enormous data and then understanding the meaning of the data. Data mining helps predict future trends which allow businesses to make
An Association analysis is used to show the relationships between people, groups, or organizations to show criminal or non-criminal activity. The association matrix is used as an interim product that includes police reports, surveillance reports, field interviews, corporate records, testimony, informant data, public record data, and other information. The association analysis can be used to indicate other possible criminal activity.