[ad_1]
Data stream mining extracts information from an active stream of data without interrupting the flow. It can involve all types of data, and accurately predicts how to locate desired information. Examples include ATM transactions and web research. The main benefit is the ability to access and search data without prohibiting others from using it.
Data stream mining is a strategy that involves identifying and extracting information from an active stream of data. With this approach, the idea is to extract the data without creating any kind of interruption in the flow itself, while also allowing others to use the data even while the extraction is in progress. This type of data stream mining activity can involve all types of data, from voice to video transmission over the Internet and even everyday activities such as withdrawing money from a bank account using an ATM or holding a telephone conversation.
One of the characteristics of data stream mining is the ability to accurately project or predict how to locate the desired information and what type of knowledge discovery tools will help to successfully locate and extract the desired information. For example, when a customer initiates a transaction using an ATM, machine programming initiates a search for relevant account information, locates the data, and then determines whether the transaction amount will reduce the account balance below an amount allowed, depending on how the account is structured. From there, the programming can return relevant data to the user, such as documenting the successful completion of the requested transaction and providing the remaining account balance after posting the credit or debit involved in the transaction.
Another common example of data stream mining is basic web research using a browser. With this application, the end user enters search values into a field, and the software that drives the browser tries to interpret those values and return data that has some relevance to the search criteria. Depending on how your browser is configured, it may also include a feature that tries to anticipate the intent of the search being conducted and offers additional words or phrases that can help refine your search to your liking. Once the user has settled on the search phrase, the browser returns the results in ranking order, using algorithms relevant to the configuration of the browser itself.
One of the main benefits of data stream mining is the ability to access and search the data without prohibiting others from using the same data. Since the data streams are constantly updating, the extraction results can change from time to time. For example, conducting a web search using a specific search phrase may produce one set of results today, but provide a slightly different set of results tomorrow, based on what new information has entered the data stream and how the engine research classifies this data.
[ad_2]