... BASED DATAMINING TECHNIQUES The objective of datamining is to extract valuable information from one’s data, to discover the ‘hiddengold’. In Decision Support Management terminology, datamining ... one search for patterns of information in data (Parsaye, 1997).Figure 2: Rule Induction process Data miningtechniques are based on data retention and data distillation. Rule induction models ... process.REFERENCES[1] Akeel Al-Attar, 1998, DataMining – Beyond Algorithms’, http://www.attar.com/tutor /mining. htm.[2] Berry, J. A. Michael; Linoff, Gordon, 1997, DataMining Techniques: For Marketing, Sales,...
... level data, 96 publications Building the Data Warehouse (Bill Inmon), 474 Business Modeling and DataMining (Dorian Pyle), 60 Data Preparation for DataMining (Dorian Pyle), 75 The Data ... Business Modeling and Data Mining, 60 Data Preparation for Data Mining, 75 470643 bindex.qxd 3/8/04 11:08 AM Page 619C Index 619 calculations, probabilities, 133–135 call detail databases, 37 call-center ... discussed, 7 Data Preparation for DataMining (Dorian Pyle), 75 The Data Warehouse Toolkit (Ralph Kimball), 474 data warehousing customer patterns, 5 for decision support, 13 discussed, 4 database...
... them. How DataMining Is Being Used Today This whirlwind tour of a few interesting applications of datamining is intended to demonstrate the wide applicability of the dataminingtechniques ... of DataMining 33 Table 2.1 DataMining Differs from Typical Operational Business Processes TYPICAL OPERATIONAL SYSTEM DATAMINING SYSTEM Operations and reports on Analysis on historical data ... the datamining solu-tion is more than just a set of powerful techniques and data structures. The techniques have to be applied in the right areas, on the right data. The virtuous cycle of data...
... process.REFERENCES[1] Akeel Al-Attar, 1998, DataMining – Beyond Algorithms’, http://www.attar.com/tutor /mining. htm.[2] Berry, J. A. Michael; Linoff, Gordon, 1997, DataMining Techniques: For Marketing, Sales, ... of Data Set(training and test set)Filling theempty cellsMUSAFinal AnalysisIs the Data SetComplete?YesNoSelection of completequestionnaires CUSTOMER SATISFACTION USING DATA MINING TECHNIQUES Nikolaos ... Analysis(Consistent family of criteria)Development of questionnaireSurveyMUSA Data Mining Search EnginesRule Induction Engine Data Mining GlobalSatisfaction PredicctionSatisfactionFunctionsPatterns...
... the mining tool the customer had selected, causing repeated mining software failures and system crashes during mining. The data reduction methodology described above reduced the data ... density manifold stability. But here is where data preparation steps into the data survey. The data survey (Chapter 11) examines the data set as a whole from many different points of view. ... rather than data preparation? Data preparation concentrates on transforming and adjusting variables’ values to ensure maximum information exposure. Data surveying concentrates on examining a...
... resampling techniques. These techniques do not affect data preparation since they are only properly applied to already prepared data. However, there is one data preparation technique used when data ... can be used to examine data as instances, data as variables, the data set as a whole, and various parts of a data set. Entropy and mutual information are used to evaluate data in many ways. Some ... Such data has a perspective. When mining perspectival data sets, it is very important to use nonperspectival test and evaluation sets. With the best of intentions, the miningdata has...
... Linoff. DataMining Techniques: For ~Marketing, Sales, and Customer Support. New York: John Wiley & Sons, 1997. This book provides a conceptual overview of various datamining techniques, ... test data set (top) and an 85.8283% accuracy in the test data for the prepared data set (bottom). 12.4 Practical Use of Data Preparation and Prepared Data How does a miner use data ... working with the data. When the data is easy to model, better models come out faster, which is the technical purpose of data preparation. How does data preparation make the data easier to work...
... Linoff. DataMining Techniques: For ~Marketing, Sales, and Customer Support. New York: John Wiley & Sons, 1997. This book provides a conceptual overview of various datamining techniques, ... Data preparation looked at here has dealt with data in the form collected in mainly corporate databases. Clearly this is where the focus is today, and it is also the sort of data on which data ... datamining tools and data modeling tools focus. The near future will see the development of automated data preparation tools for series data. Approaches for automated series data preparation...
... required for mining distributed data, handling the meta -data and the mappings required for mining the distributed data. Spatial database systems involve spatial data - that ... algorithms and is termed distributed data mining [51].Traditional data mining algorithms require all data to be mined in a single,centralized data warehouse. A fundamental challenge ... with a data mining system. Thus the development of efficient compression techniques, particularly suitable for data mining, will continue to be a design challengefor advanced database...
... of DataMining 33 Table 2.1 DataMining Differs from Typical Operational Business Processes TYPICAL OPERATIONAL SYSTEM DATAMINING SYSTEM Operations and reports on Analysis on historical data ... of techniques to apply in a particular situation depends on the nature of the datamining task, the nature of the available data, and the skills and preferences of the data miner. Data mining ... that, on a technical level, the datamining effort is working and the data is reasonably accurate. This can be quite comforting. If the data and the dataminingtechniques applied to it are powerful...
... Applications and Trends in DataMining 64911.1 DataMining Applications 64911.1.1 DataMining for Financial Data Analysis 64911.1.2 DataMining for the Retail Industry 65111.1.3 DataMining for the Telecommunication ... Commercial DataMining Systems 66311.3 Additional Themes on DataMining 66511.3.1 Theoretical Foundations of DataMining 66511.3.2 Statistical DataMining 66611.3.3 Visual and Audio DataMining ... Motivated Data Mining? Why Is It Important? 11.2 So, What Is Data Mining? 51.3 DataMining On What Kind of Data? 91.3.1 Relational Databases 101.3.2 Data Warehouses 121.3.3 Transactional Databases...
... development, 198–203D Data types of, 26–27validation, 152–155 Data errors and outliers, 60, 62–64, 69 Data marts, 31 Data mining software classification trees, 98 Data preparation for modeling. ... 23–24Solicitation mail, 31Sources of data, 27–36.See also Data sources selectingcustomer database, 28–29 data warehouse, 31–35external, 36internal, 27–35offer history database, 30–31solicitation ... See Preparing data for modeling Data requirements review and evaluation, 187–188 Data sources selecting, 25–48constructing modeling data set, 44–48for modeling, 36–44sources of data, 27–36summary...
... c04.qxd 3/8/04 11:10 AM Page 97 Data Mining Applications 97 mining techniques used to generate the scores. It is worth noting, however, that many of the dataminingtechniques in this book can ... relationships suggest new hypotheses to test and the datamining process begins all over again. Lessons Learned Data mining comes in two forms. Directed datamining involves searching through historical ... independent of the data 470643 c04.qxd 3/8/04 11:10 AM Page 87 Data Mining Applications in Marketing and Customer Relationship Management 4 CHAPTER Some people find dataminingtechniques interesting...