diaper and beer reflect the huge data processing time

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As information technology continues to evolve, peopleuse information technology to process data of the large increase in capacity,more and more databases are used in business management, production control andengineering design and other areas. However, the face of ever-increasingvariety of complex data, already exists in the database query functions can nolonger meet people's needs, can extract from the data that people needinformation and knowledge is our growing concern. Traditional statisticaltechniques have been facing tremendous challenges, set of statistics,databases, knowledge discovery technology in a data mining technologies haveemerged. In recent years, data mining technology in the retail, directmarketing, manufacturing, finance finance, insurance, communications andmedical services, etc., are widely used.
  
! j! S: X$ @4 T/ B. ^First, the basic concepts of data mining

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(一) "beer, diaper," a classic case
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In understanding the concept of data mining, we first look at a "beer diaper" story. Wal-Mart in this story the protagonist is the world's largest retailer, in its thousands of supermarkets across the United States, children diapers and beer actually placed side by side together on the prices of goods in the nearby sales, and both have pretty good sales . Wal-Mart through the establishment of the original data warehouse, analysis of the original transaction data, according to product sales cycle, statistical information, and then use data mining tools for analysis and digging and found that Wal-Mart supermarket chains weekends the sales of beer and diapers is very large. Further investigation showed that families with children in the United States, his wife often asked their husbands to work and after going to buy diapers for their children, while their husbands were in the After buying diapers then smoothly back to his own beer drinkers, beer and diapers together with the opportunity to buy the most. After the store to break the routine will be placed on the shelves of beer and diapers together, making beer and diaper sales to grow further. Beer and diapers these two seemingly unrelated, but in certain conditions, there is a close relationship between them, which is data mining techniques. ..
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(二) The concept of data mining
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Data Mining (Data Mining) is from vast amounts of raw data, to identify implicit in them, however, we do not know, but is potentially significant knowledge and information in order to use this knowledge to guide our activities. From the statistical point of view, data mining can be seen as a large number of the complex through computer automated exploratory data analysis. With the rapid development of information technology, it is a sharp increase in the amount of data accumulated. Data Mining is to comply with this need came into being developed data processing techniques.
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Second, the retail application data mining background
  
' I) c5 F4 r! Q5 q/ b! bRetail customer relationship management ((Customer Relationship Management. CRM) is a customer-centric marketing concepts and strategies. CRM objective is to reduce the sales cycle and marketing costs, increase revenue, expand their business needed to find new markets and channels and enhance customer price, satisfaction, profitability and loyalty. retail customer relationship management, primarily through bar codes, sales management system, customer data management system for a variety of ways to obtain information on product information, customer information, supplier information and shops information a lot of data, how to use the mass data analysis of which items will sell, what products do not sell, what customers suitable for what commodities, how the mix between, is to enable retailers headache. use of data mining tools an analysis of these data can help retailers to scientific decision-making, an analysis of what products customers purchase together with the most promising, thus placing these products together; analysis of product sales trends, thus providing retailers purchase recommendations; analysis of purchase commodities, personnel information to help retailers choose the location of the shop and so on.
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3, data mining techniques commonly used algorithm for
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/ P' F4 u" y+ E. a+ K  H4 A" a4 JData mining is the core technology in the retail CRM, through the analysis of customers who have purchased goods and the intrinsic link between these products to determine the customer's buying habits and tendencies associated with buying, helping retailers to develop marketing strategies. In order to achieve in the retail sector .. CRM application, data mining technology, mainly related to the following commonly used algorithms: ..

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(一) clustering analysis algorithm
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Clustering analysis algorithm is based on the characteristics of things, their clustering or classification, that is, the so-called feather flock together, with a view from the laws and the typical patterns found. In the retail sector, the cluster analysis can help the market analysts to distinguish from the consumer database to a different consumer groups, and summarized for each category of consumer spending patterns or habits. ..
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(二) Decision Tree Algorithm
  
Decision tree algorithm is the use of the training set to generate a test function, according to different values of the establishment of a branch of the tree; in each branch of the creation of duplicate subset of the lower nodes and branches, thus generating a decision tree. Then the decision tree for pruning treatment and finally the decision tree into a rule. Decision tree algorithm is commonly used in the prediction model, which has the purpose of large amounts of data by classification, to find some valuable potential information. Classify it fast, especially for large-scale data classification. .

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(三) neural network algorithm
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3 y! ~. j. n( K. WNeural network algorithms to simulate the human neuronal function, through the input layer, hidden layer, output layer and so on, to adjust the data to calculate the final yield results. Neural network algorithm has the advantage that it can accurately predict the complex issues. Itself has a good robustness, adaptive and highly fault-tolerant. .. Http://www.itonghui.com
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(四) association rule mining algorithm
  
Association rule mining is used to detect the correlation between attributes in the database connection algorithm. Association rule discovery is the essence of the task was found in the database, strong association rules, use of these association rules to understand customer behavior, the most typical example is market basket analysis.
  
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4, data mining technology in the retail application
  
With the growing rise of Web or e-commerce methods, retail CRM is the main application areas of data mining. Data mining technology can help to identify customer buying behavior, found that customer buying patterns and trends, improve service quality, achieve better customer retention and satisfaction, improve goods sales ratio, design better products transportation and distribution strategy to reduce business costs. Data Mining Application of CRM in the retail industry is mainly reflected in the following areas:

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(一) The use of multi-feature data cube for sales, customer, product, time and regional multi-dimensional analysis of
  
+ r7 d- U4 a; y8 `Multidimensional data analysis is the way through the multi-dimensional analysis of the data, query and reporting. Dimension is one specific point of observation data. For example, companies considering the sale of products, usually from the customer, product, time and regional perspective of insight into the different product sales. Here customers, products, time and area is the dimension. According to different combinations of these dimensions and the study of metrics from the customer found in the basic library of different customer base, so that decision-makers according to the characteristics of the main customer base, accordingly, orders, sales and service decision-making. .. Http://www.dmresearch.net/bbs
  
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