Text Data Mining

Data mining is simply filtering through large amounts of raw data for useful information that gives businesses a competitive edge. This information is made up of meaningful patterns and trends that are already in the data but were previously unseen.

The most popular tool used mining is artificial intelligence (AI). AI technologies try to work the way the human brain works, by making intelligent guesses, learning by example, and using deductive reasoning. Some of the more popular AI methods used in data mining include neural networks, clustering, and decision trees.

Neural networks look at the rules of using data, which are based on the connections found or on a sample set of data. As a result, the software continually analyses value and compares it to the other factors, and it compares these factors repeatedly until in finds patterns emerging. These patterns are known as rules. The software then looks for other patterns based on these rules or sends out an alarm when a trigger value is hit.

Clustering divides data into groups based on similar features or limited data ranges. Clusters are used when data isn’t labelled in a way that is favourable to mining. For instance, an insurance company that wants to find instances of fraud wouldn’t have its records labelled as fraudulent or not fraudulent. But after analyzing patterns within clusters, the mining software can start to figure out the rules that point to which claims are likely to be false.

Decision trees, like clusters, separate the data into subsets and then analyse the subsets to divide them into further subsets, and so on (for a few more levels). The final subsets are then small enough that the mining process can find interesting patterns and relationships within the data. Once the data to be mined is identified, it should be cleansed. Cleansing data frees in from duplicate information and erroneous data. Next, the data should be stored in a uniform format within relevant categories or fields. Mining tools can work with all types of data storage, from large data warehouses to smaller desktop databases to flat files. Data warehouses and data marts are storage methods that involve archiving large amounts of data in a way that makes it easy to access when necessary.

When the process in complete, the mining software generates a report. An analyst goes over the report to see if further work needs to be done, such as refining parameters, using other data analyst tools to examine the data, or even scrapping the data if it’s unusable. If no further work is required, the report proceeds to the decision makers for appropriate action.

The power of data mining is being used for many purposes, such as analyzing Supreme Court decisions, discovering patterns in health care, pulling stories about competitors from newswires, resolving bottlenecks in production processes, and analyzing sequences in the human genetic makeup. There really is no limit to the type of business or area of study where data mining can be beneficial.

Ex.1. Find the answers to these questions in the following text.

What tool is other used in data mining?
What AI method is used for the following processes?

Separate data into subsets and then analyse the subsets to divide them into further subsets for a number of levels.
Continually analyse and compare data until patterns emerge.
Divide data into groups based on similar features or limited data ranges.

What term is used for the patterns found by neural networks?
When are clusters used in data mining?
What types of data storage can be used in data mining?
What can an analyst do to improve the data mining results?
Name some of the ways in which data mining is currently used.

Ex.2. Match the terms with the statements.

Data mining
AI

Cleansed data
Data warehouse

Storage method of archiving large amounts of data to make it easy to access.
Data free from duplicate and erroneouse information.
A process of filtering through large amounts of raw data for useful information.
A computing tool that tries to operative in a way similar to the human brain.

Ex.3. Mark the following as True or False.

Data mining is a process of analysing known patterns in data.
Artificial intelligence is commonly used in data mining.
In data mining, patterns found while analyzing data are used for further analyzing the data.
Data mining is used to detect false insurance claims.
Data mining is only useful for a limited range of problem.

Ex.4. Complete the following description of the data mining process using words from the text:

Large amounts of data stored in data _______ are often used for data _______. The data is first _______ to remove _______ information and errors. The ______ is then analysed using a tool such as _____ _____. An analysis report is then analysed by an _____ who decides if the _____ need to be refined, other data _____ tools need to be used, or if the results need to be discarded because they are _____ . The analyst passes the final results to the ______ makers who decide on the _________ action.

Ex.5. Complete the gaps in this summary of the text on operating systems using these linking words and phrases:

Although

Because

but

In addition

Such as

therefore

The user is aware of the effects of different applications programs _____ operating systems are invisible to most users. They lie between applications programs, ______ wordprocessing, and the hardware. The supervisor program is the most important. It remains in memory, _______it is referred to as resident. Others are called non-resident _____ they are loaded into memory only when needed. Operating systems manage the computer’s resources, ______ the central processing unit. ______, they establish a user interface, and execute and provide services for applications software. ______ input and output operations are invoked by applications programs, they are carried out by the operating system.

Ex.6. Try to find the commands from the lists below which will have these actions.

VMS

Help