عنوان انگلیسی مقاله:

Analysis the effect of data mining techniques on database

ترجمه عنوان مقاله: تحلیل تاثیر تکنیک های استخراج داده بر پایگاه داده ها

رشته: فناوری اطلاعات

سال انتشار: 2012

تعداد صفحات مقاله انگلیسی: 6 صفحه

منبع: الزویر و ساینس دایرکت

نوع فایل: pdf

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چکیده انگلیسی مقاله

In today’s information society, we witness an explosive growth of the amount of information becoming available in electronic form and stored in large databases. Data mining can help in discovering knowledge. Data mining can dig out valuable information from databases in approaching knowledge discovery and improving business intelligence. In this paper, we have discussed the involvement and effect of data mining techniques on relational database systems, and how its services are accessible in databases, which tool we require to use it, with its major pros and cons in various databases. Through all this discussion we have presented how database technology can be integrated to data mining techniques.
Keywords: Data acquisition, Databases,Data warehouse, Data mining, Data miner, Intelligent miner

مقدمه انگلیسی مقاله

In recent years data mining has become a very popular technique for extracting information from the database in different areas due to its flexibility of working on any kind of databases and also due to the surprising results [1].

Data mining is the search for valuable information in large volumes of data [1]. With the increase of availability of databases containing structures, mining techniques especially designed for this type of data are becoming more and more important [2]. To improve both software productivity and quality, software engineers are increasingly applying data mining algorithms to various Software Engineering tasks [3].

The progress in data acquisition and successful development of storage technology at cheaper rates, along with limited human capabilities in analyzing and understanding big databases have tempted scientists and researchers to move forward towards the specific field of knowledge discovery in databases (KDD). The huge amount of available data, jointly with a poor understanding of the processes that have generated them, enforces the use of data mining techniques to extract frequent structural patterns that may convey important information [2].

Databases are too big, and data mining can help to extract interesting knowledge from data in large collections. But still we are not completely aware about how to use data mining, and with which database it works well. This paper discuss about data mining technique with respect to different databases. It is just like a comparative study of various databases regarding how we can use data mining techniques on database technology.

Despite the potential effectiveness of data mining to significantly enhance data analysis, this technology is destined be a niche technology unless an effort is made to integrate this technology with traditional database systems. This is because data analysis needs to be consolidated at the warehouse for data integrity and management concerns. Therefore, one of the key challenges is to enable integration of data mining technology seamlessly within the framework of traditional database systems.

Till now, researches are going on in this technique to use it in an efficient manner to get desirable results in database technology. In this paper, we introduce IBM DB2, Microsoft SQL Server, MYSQL, and ORACLE for Data mining. Data mining techniques, based on statistics and machine learning can significantly boost the ability to analyze data.

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