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Title      : MSCS-516A Data Mining
Subject      : Computer Science
copyright © 2018   : Karnataka State Open University
Author      : KSOU
Publisher      : Karnataka State Open University
Chapters/Pages      : 22/279
Total Price      : Rs.      : 208
 
 
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Chapters
     
What is Data Warehouse? A Multidimensional Data Model Total views (319)  
The concept of data warehousing has evolved out of the need for easy access to a structured store of quality data that can be used for decision making. It is globally accepted that information is a very powerful asset that can provide significant benefits to any organization and a competitive advantage in the business world. Organizations have vast amounts of data but have found it increasingly d ......
Pages: 10
Price: Rs 0   
 
Data Warehousing Architecture Total views (319)  
It is easy to think of the data warehouse as just a big collection of data, in fact delivering an effective data warehouse requires a large set of related capabilities. Data is the fundamental component, cleaned, organized data, mostly extracted from the campus operational systems. Making that data useful to a variety of campus personnel, though, requires some applications to deliver and explain i ......
Pages: 10
Price: Rs 7.5   
 
Data Warehouse Implementation Total views (330)  
Data warehouses contain huge volumes of data. OLAP engines demand that decision support queries be answered in'the order of seconds. Therefore, it is crucial for data warehouse systems to support highly efficient cube computation techniques, access methods, and query processing techniques. How can this be done?, you may wonder. In this unit, we examine methods for the efficient implementation of d ......
Pages: 10
Price: Rs 7.5   
 
Data Cube Technology Total views (329)  
Data warehouses and OLAP tools are based on a multidimensional data model. This model views data in the form of a data cube. In this section, you will learn how data cubes model n-dimensional data. You will also learn about concept hierarchies and how they can be used in basic OLAP operations to allow interactive mining at multiple levels of abstraction.
Pages: 9
Price: Rs 6.75   
 
Data Mining Application, Data Mining System Products and Research Prototypes Total views (790)  
Data Mining is the exploration and analysis of large sets, in order to discover meaningful patterns and rules. The key idea is to find effective ways to combine computers power to process data with the human eye's ability to detect patterns. The techniques of data mining are designed for work best with large data sets. Since Data Mining is a young discipline with wide and diverse applications, th ......
Pages: 9
Price: Rs 6.75   
 
Additional Themes on Data Mining Total views (790)  
At the end of this unit, students will be able to explain audio data mining and understand the concept of statistical data mining.They will also be able to discuss video data mining.
Pages: 10
Price: Rs 7.5   
 
Data Mining and Intelligent Query Answering Total views (787)  
At the end of this unit,students will be able to explain information analysis and discuss intelligent information delivery.
Pages: 10
Price: Rs 7.5   
 
Cluster Analysis and Types of Cluster Analysis Total views (768)  
Clustering is the process of grouping the data into classes or clusters, so that objects within a cluster have high similarity in comparison to one another but are very dissimilar to objects in other clusters. Dissimilarities are assessed based on the attribute values describing the objects. Often, distance measures are used. Clustering has its roots in many areas, including data mining, statisti ......
Pages: 17
Price: Rs 12.75   
 
Categorization of Major Clustering Methods Total views (765)  
There exit a large number of clustering algorithms in the literature. The choice of clustering algorithm depends both on the type of data available and on the particular purpose and application. If cluster analysis is used as a descriptive or exploratory tool, it is possible to try several algorithms on the same data to·see what the data may disclose.
Pages: 15
Price: Rs 11.25   
 
Density Based and Model Based Clustering Total views (774)  
Model-based methods hypothesize a model for each of the clusters and find the best fit of the data to the given model. A model- based method hypothesize a model for each of the clusters and find the best fit of the data to the given model A model-based algorithm may locate clusters by constructing a density function that reflects the spatial distribution of the data points.
Pages: 14
Price: Rs 10.5   
 
Neural Network Approach and Outer Analysis Total views (763)  
Neural networks have seen an explosion of interest over the last few years, and are being successfully applied across an extraordinary range of problem domains, in areas as diverse as finance, medicine, engineering, geology and physics, Indeed, anywhere that there are problems of prediction, classification or control, neural networks are being introduced. This sweeping success can be attributed to ......
Pages: 13
Price: Rs 9.75   
 
Association Rule Mining Total views (729)  
Association rule mining finds interesting association or correlation relationships among a large set of data items. With massive amounts of data continuously being collected and stored, many industries are becoming interested in mining association huge amounts of business transaction records can help in many business decision making processes, such as catalog design, cross marketing,and loss-leade ......
Pages: 13
Price: Rs 9.75   
 
Mining Single - Dimensional Boolean Association Rules From Transactional Databases Total views (734)  
In this section, students will learn methods for mining the simplest form of frequent patterns-single dimensional,single-level, Boolean frequent item sets, such as those discussed for market basket analysis in the earlier chapter. We begin by presenting Apriori, a basic algorithm for finding frequent item sets; we look at how to generate strong association rules from frequent item sets.We will de ......
Pages: 17
Price: Rs 12.75   
 
Mining Multilevel Association Rules from Transaction Databases Total views (733)  
For many applications, it is difficult to find strong associations among data items at low or primitive levels of abstraction due to the sparsity of data in multidimensional space. Strong associations discovered at very high concept levels may represent common sense knowledge. However, what may represent common sense to one user may seem novel to another. Therefore,data mining systems should prov ......
Pages: 10
Price: Rs 7.5   
 
Data Mining Parameters Total views (726)  
A popular misconception about data mining is to expect that data mining systems can autonomously dig out all of the valuable knowledge that is embedded in a given large database,without human intervention or guidance. Although it may at first sound appealing to have an autonomous data mining system, in practice, such systems will uncover an overwhelmingly large set of patterns. A data-mining task ......
Pages: 15
Price: Rs 11.25   
 
Presentation and Visualization of Discovered Pattern Total views (724)  
For data mining to be effective, data mining systems should be able to display the discovered patterns in multiple focus, such as rules, tables, cross-tabs, pie or bar charts, decision trees, cubes,or other visual representations. Allowing the visualization of discovered patterns in various forms can help users with different backgrounds to identify patterns of interest and to interact or guide t ......
Pages: 6
Price: Rs 4.5   
 
Data Mining Query Language Total views (726)  
The feature of the data mining systems is the ability to support ad-hoc and interactive data mining in order to facilitate flexible and effective knowledge discovery. Data mining query languages can be designed to support such a feature. The importance of the design of a good data mining query language can also be seen from observing the history of relational database systems. Relational database ......
Pages: 22
Price: Rs 16.5   
 
Data Warehousing to Data Mining Total views (733)  
Data mining is concerned with finding hidden relationships present in business data to allow businesses to make predictions for future use. It is the process of data-driven extraction of not so obvious but useful information from large databases. Data mining has emerged as key business intelligence technology.
Pages: 21
Price: Rs 15.75   
 
Data Mining Functionalities and Data Cleaning Total views (735)  
Data mining functionalities are used to specify the kind of patterns to be found in data mining tasks. In general, data mining tasks can be classified into two categories: descriptive and predictive. Descriptive mining tasks characterize the general properties of the data in the database. Predictive mining tasks perform inference on the current data in order to make predictions.
Pages: 15
Price: Rs 11.25   
 
Data Integration and Transformation Total views (735)  
Data mining often requires data integration-the merging of data from multiple data stores. The data may also need to be transformed into forms appropriate for mining. This section describes both data integration and data transformation.
Pages: 10
Price: Rs 7.5   
 
Data Reduction Total views (738)  
Data reduction techniques can be applied to obtain a reduced representation of the data set that is much smaller in volume, yet closely maintains the integrity of the original data. That is, mining on the reduced data set should be more efficient yet produce the same (or almost the same)analytical results.
Pages: 13
Price: Rs 9.75   
 
Trends in Data Mining Total views (741)  
The diversity of data, data mining tasks, and data mining approaches poses many challenging research issues in data mining. The development of efficient and effective data mining methods and systems, the construction of interactive and integrated data mining environments, the design of data mining languages, and the application of data mining techniques to solve large application problems are impo ......
Pages: 10
Price: Rs 7.5   
 


 
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