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标题: diaper and beer reflect the huge data processing time [打印本页]

作者: wangzheng3056 时间: 2013-8-24 10:45
标题: diaper and beer reflect the huge data processing time
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.

First, the basic concepts of data mining

作者: wangzheng3056 时间: 2013-8-24 10:46
(一) "beer, diaper," a classic case

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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作者: wangzheng3056 时间: 2013-8-24 10:46
(二) The concept of data mining

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.

Second, the retail application data mining background

Retail 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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作者: wangzheng3056 时间: 2013-8-24 10:46
3, data mining techniques commonly used algorithm for

Data 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: ..

作者: wangzheng3056 时间: 2013-8-24 10:46
(一) clustering analysis algorithm

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. ..

作者: wangzheng3056 时间: 2013-8-24 10:47
(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. .

作者: wangzheng3056 时间: 2013-8-24 10:47

(三) neural network algorithm

Neural 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

作者: wangzheng3056 时间: 2013-8-24 10:47
(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.

作者: wangzheng3056 时间: 2013-8-24 10:47
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:

作者: wangzheng3056 时间: 2013-8-24 10:47
(一) The use of multi-feature data cube for sales, customer, product, time and regional multi-dimensional analysis of

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

作者: wangzheng3056 时间: 2013-8-24 10:48
(二) the use of correlation analysis of information to make a purchase recommendation for mining association and commodity reference

Correlation analysis is the use of association rules, data mining techniques, aimed at the hidden relationships between the data found in the database form, such as .. "90% of customers in a purchasing activity to purchase A purchase of merchandise B products will also "The kind of knowledge. Sales records from the Mining Association information, you can find customers to buy a particular brand is likely to purchase other commodities. Such information can be used to form a definite buy recommendation. Businesses through advocacy to improve services to help customers choose products, increase sales and reduce inventories.

作者: wangzheng3056 时间: 2013-8-24 10:48
(三) The use of multi-dimensional analysis and correlation analysis to analyze the effectiveness of promotional activities

The use of multi-dimensional analysis and correlation analysis examined data from the database to analyze customer buying habits, advertising success rate, and other strategic information. By searching the database using a database of sales data in recent years, using multi-dimensional correlation analysis method, by comparing the sales volume of sales and number of transactions during the period and promotional activities before and after the situation, predictable seasonal and monthly sales, variety of goods and inventory trends analysis could also determine the bargains, and the number and operation of the decision-making. Moreover, the correlation analysis can find out which products can be used for promotional activities, to facilitate arrangements for supply of goods and improve sales.

作者: wangzheng3056 时间: 2013-8-24 10:48
(四) sequential pattern mining can be used for customer loyalty analysis

Sequential pattern analysis and correlation analysis of similar, but the focus is on analysis of data before and after the sequence of the relationship between. Sequential pattern mining can be used to analyze the customer's loyalty to the changes in consumption or by which the price and variety of goods to be adjusted to retain old customers and attract new customers, to guarantee a certain number of customers. Merchants from the original client but later converted to competitor's customer base, analyze its characteristics, then the results of the analysis to existing customer data to identify possible shift in customers, and then devise methods to prevent the loss of customers; also according to customer's Consumer behavior and transaction records to sort of customer loyalty, according to the level of wastage and thus with different strategies.
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作者: wangzheng3056 时间: 2013-8-24 10:48
(五) the use of cross-selling model to sell existing customers new products or services

Retail and customer relationship is an ongoing, developmental, and cross-selling is the selling point to customers a new product or service process. Cross-selling is based on buyers and sellers based on the principle of mutual benefit, the customer due to get more and better services to meet their needs benefit, enterprises can also benefit from the result of sales growth. Cross-selling advantage, businesses can more easily get more customers a wealth of information. Enterprise master customer information, especially the information prior to purchase, may be decided that the customers with the next purchase of critical information. At this time reflects the role of data mining, it can help businesses find customer buying behavior that affect the information and factors.

作者: WXYINHIT 时间: 2014-1-9 17:26
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