Impact of Duo-Mining in Knowledge Discovery Process

Duo mining is used frequently in a mixture of indu stries and its enduring to gain in both popularity and acceptance. DuoMining is basically a blend of data and text mining . This paper suggests Data mining architecture in a ddition with Knowledge discovery process. It also presents the comparison between data mining and text mining. As Data minin g handles various processes like text Mining, Multi-media, Web mining etc.Text Classification, Clustering, Keyword based Associati on are the terms that are used to describe the process of Text Mining. I. DUOMINING Duo-Mining is the variation of data and text mining. It has demonstrated especially well for the banking and credit card companies in order to take better decisions.As separate capabilities, of the patternfinding technologies of data mining and text mining have been around for years. However, it is only recently that enterprises have been started to use the two in acycle and have discovered that it is a combination that is worth more than the sum of its parts. [1] They are similar because they both"mine" large amounts of data, and looking for significant patterns. However, what they evaluate is quite different. Instead of only being able to analyze the structured data they collect from transactions, they can add call logs from customer services and further analyze customers and spending patterns from the text mining side. These new developments in text mining technology that go beyond simple searching methods are the key to information discovery which is generally work on the unstructured data. II. DATA MINING AND ITS TASKS Today Data Mining is used everywhere in a collection of data and its availability and accessibi lity. But why We use Data Mining. • Explosive growth of data from terabytes to pet bytes • Data gathering and data accessibility. • Traditional techniques are infeasible for unprocessed data. [2] Data mining is the process of extracting patterns from large data sets bycombining ofmethods from figures and artificialintelligence withthe database management system. Data mining is seen as an increasingly important tool by modern business to transform data into business intelligence giving an informational advantage. It is currently used in a wide range of theprofiling practices, such as marketing, surveillance, fraud recognition and methodicaldiscovery . The related terms data dredging, data fishing and data snooping refer to the use of data mining techniques to sample portions of the larger population International Journal of Computer Science & Informatics (IJCSI), ISSN (PRINT) : 2231–5292, Vol.2, Issue-4