growing researches in data mining as a part of education. This new developing field, called Educational Data Mining, concerns with creating techniques that find information from data originate from educational situations. The data can be collected structure verifiable and operational data dwell in the databases of educational establishments. The understudy data can be close to home or scholastic. Additionally it can be gathered from e-learning frameworks which have a vast measure of data utilized by mostly…

Text mining sometimes known as text data mining often refers to the process of pulling out of interesting and non-trivial patterns of knowledge form a semi or unstructured text document. Text mining can also serve as an extension of data mining or of data finding from a structures database. With text mining it can be the same as data mining but with a bit more complexity, because they somewhat carry out the same processes and has the same purpose, however with text mining the data is more unstructured…

Abstract Data Mining is the non-trivial extraction of potentially useful information about data. In other words, Data Mining extracts the knowledge or interesting information from large set of structured data that are from different sources. There are various research domains in data mining specifically text mining, web mining, image mining, sequence mining, process mining, graph mining, etc. Data mining applications are used in a range of areas such as it is used for financial data analysis, retail…

topics, areas and works related to the research presented here. we conduct a brief but comprehensive in depth review of data mining and association rule mining approaches and techniques, followed by a focus at interestingness & quality, and redundancy issues related to association rule mining. This review sets the basic work for our research and the proposals made here. 2.1 Data mining Data Mining technique is the result of a long process of studies and research in the area of databases and product…

Data stream mining is a stimulating field of study that has raised challenges and research issues to be addressed by the database and data mining communities. The following is a discussion of both addressed and open research issues [19]. Handling the continuous flow of data streams This is a data management issue. Traditional database management systems are not capable of dealing with such continuous high data rate. Novel indexing, storage and querying techniques are required to handle this non…

Data Mining: What is Data Mining? Overview Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified…

Market Research Research Methods & Data Mining A Bottled Water survey done by Mintel, in spring of 2015, found mid-priced brands show the highest market penetration. 68% of bottled water drinkers surveyed by Mintel say that they usually drink mid-priced brands. More than half of those surveyed said they usually drink value brands, showing a definite consumer preference towards mid-and value-priced brands on the market. Only 13% of those surveyed drank Premium water. (Mintel Group Ltd. 2015) Enhancements…

is text mining different than data mining? Text mining is a process which collects information and knowledge from large amounts of unstructured data sources. When I say unstructured data sources, I am talking about Pdf files, Word documents, XML files, text excerpts etc… Text mining collects information from text. Text mining is different than data mining because data mining is a process which collects information and knowledge from large amounts of structured data sources. Structured data sources…

Abstract. Data mining is concerned with analysing large volumes of (often unstructured) data to automatically discover interesting regularities or relationships which in turn lead to better understanding of the underlying processes. The field of temporal data mining is concerned with such analysis in the case of ordered data streams with temporal interdependencies. Over the last decade many interesting techniques of temporal data mining were proposed and shown to be useful in many applications. Since…

Data mining is the process of discovering patterns, trends, correlations from large amounts of data stored electronically in repositories, using statistical methods, mathematical formulas, and pattern recognition technologies (Sharma n.d.). The main idea is to analyze data from different perspectives and discover useful trends, patterns and associations. As discussed in the previous chapter, the healthcare organizations are producing massive amounts of electronic medical records, which are impossible…