AUTOMATIC ORDERING BY ESTIMATING FREQUENT PRODUCTS IN ONLINE STORE USING DATA MINING:
OVERVIEW:
Data Mining is defined as extracting information from huge sets of data. In other words, we can say that data mining is the procedure of mining knowledge from data. Data mining is highly useful in the following domains.
• Market Analysis and Management
• Corporate Analysis & Risk Management
• Fraud Detection
User Interface may be any website. A product is searched in the Database, Database Warehouse, World Wide Web and other repository. This means that the data searched will be fetched from all over net.
The data will then be cleansed to avoid noise, error in data and unwanted data with the help of parser. Then the selective data will be integrated and all the data will be fetched by Data Ware House Server. With the help of knowledge base and pattern evaluation, the result will be given to interface.
‘Amazon’ as an example to understand it better. If a user has sent request to a User Interface (Amazon) to search for a phone within the range of a defined amount, then it will search in its Knowledge Base (similar kind of information is stored) for similar requests processed earlier.
If the same pattern is evaluated, then the result will be given to the user with the help of data-mining engine which will further ask data warehouse server to fetch phone within range of that searched amount.
It will also search all over the net and then it will clean, integrate and give details back to data-mining engine. It will also store the information it in its knowledge base for future trend analysis. Post this process, the interface will be provided the desired result.
Market Analysis and Management:
Listed below are the various fields of market where data mining is used −
Customer Profiling − Data mining helps determine what kind of people buy what kind of products.
Identifying Customer Requirements − Data mining helps in identifying the best products for different customers. It uses prediction to find the factors that may attract new customers.
Cross Market Analysis − Data mining performs Association/correlations between product sales.
Target Marketing − Data mining helps to find clusters of model customers who share the same characteristics such as interests, spending habits, income, etc.
Determining Customer purchasing pattern − Data mining helps in determining customer purchasing pattern.
Providing Summary Information − Data mining provides us various multidimensional summary reports.
AUTOMATIC ORDERING BY ESTIMATING FREQUENT PRODUCTS IN ONLINE STORE USING DATA MINING:
OVERVIEW:
Data Mining is defined as extracting information from huge sets of data. In other words, we can say that data mining is the procedure of mining knowledge from data. Data mining is highly useful in the following domains.
• Market Analysis and Management
• Corporate Analysis & Risk Management
• Fraud Detection
User Interface may be any website. A product is searched in the Database, Database Warehouse, World Wide Web and other repository. This means that the data searched will be fetched from all over net.
The data will then be cleansed to avoid noise, error in data and unwanted data with the help of parser. Then the selective data will be integrated and all the data will be fetched by Data Ware House Server. With the help of knowledge base and pattern evaluation, the result will be given to interface.
‘Amazon’ as an example to understand it better. If a user has sent request to a User Interface (Amazon) to search for a phone within the range of a defined amount, then it will search in its Knowledge Base (similar kind of information is stored) for similar requests processed earlier.
If the same pattern is evaluated, then the result will be given to the user with the help of data-mining engine which will further ask data warehouse server to fetch phone within range of that searched amount.
It will also search all over the net and then it will clean, integrate and give details back to data-mining engine. It will also store the information it in its knowledge base for future trend analysis. Post this process, the interface will be provided the desired result.
Market Analysis and Management:
Listed below are the various fields of market where data mining is used −
Customer Profiling − Data mining helps determine what kind of people buy what kind of products.
Identifying Customer Requirements − Data mining helps in identifying the best products for different customers. It uses prediction to find the factors that may attract new customers.
Cross Market Analysis − Data mining performs Association/correlations between product sales.
Target Marketing − Data mining helps to find clusters of model customers who share the same characteristics such as interests, spending habits, income, etc.
Determining Customer purchasing pattern − Data mining helps in determining customer purchasing pattern.
Providing Summary Information − Data mining provides us various multidimensional summary reports.
AUTOMATIC ORDERING BY ESTIMATING FREQUENT PRODUCTS IN ONLINE STORE USING DATA MINING:
OVERVIEW:
Data Mining is defined as extracting information from huge sets of data. In other words, we can say that data mining is the procedure of mining knowledge from data. Data mining is highly useful in the following domains.
• Market Analysis and Management
• Corporate Analysis & Risk Management
• Fraud Detection
User Interface may be any website. A product is searched in the Database, Database Warehouse, World Wide Web and other repository. This means that the data searched will be fetched from all over net.
The data will then be cleansed to avoid noise, error in data and unwanted data with the help of parser. Then the selective data will be integrated and all the data will be fetched by Data Ware House Server. With the help of knowledge base and pattern evaluation, the result will be given to interface.
‘Amazon’ as an example to understand it better. If a user has sent request to a User Interface (Amazon) to search for a phone within the range of a defined amount, then it will search in its Knowledge Base (similar kind of information is stored) for similar requests processed earlier.
If the same pattern is evaluated, then the result will be given to the user with the help of data-mining engine which will further ask data warehouse server to fetch phone within range of that searched amount.
It will also search all over the net and then it will clean, integrate and give details back to data-mining engine. It will also store the information it in its knowledge base for future trend analysis. Post this process, the interface will be provided the desired result.
Market Analysis and Management:
Listed below are the various fields of market where data mining is used −
Customer Profiling − Data mining helps determine what kind of people buy what kind of products.
Identifying Customer Requirements − Data mining helps in identifying the best products for different customers. It uses prediction to find the factors that may attract new customers.
Cross Market Analysis − Data mining performs Association/correlations between product sales.
Target Marketing − Data mining helps to find clusters of model customers who share the same characteristics such as interests, spending habits, income, etc.
Determining Customer purchasing pattern − Data mining helps in determining customer purchasing pattern.
Providing Summary Information − Data mining provides us various multidimensional summary reports.