Different Aspects of Data Mining and Information Booth Systems


Different Aspects of Data Mining and Information Booth Systems

In general, information is structured, processed and organised data that informs decision-making. It gives context to data and allows individuals to make informed decisions. For instance, a particular customer’s sale in a restaurant is information-it becomes information when the company is able to identify which dish is the most popular or least popular.

Information is of varying levels of importance depending on its purpose. For instance, an email with a subject line “urgent business” may have many levels of meaning depending on what it actually refers to. Similarly, a message received by a fax machine may have many levels of meaning depending on what it actually says. It therefore falls under the scope of Artificial Intelligence (AAI) and Data Processing Cycle (DPC).

In artificial intelligence, the aim is to achieve high levels of accuracy in the mean time that is needed for decision-making. Therefore, it is very important that data be processed accurately and in a short time. Hence, data visualization or data compression is also an aspect of artificial intelligence. When data is visualized it can be understood and compared with other data and can also be used for decision-making purposes.

In data compression, different transformations are done to the continuous data to remove unwanted information. Ordinal data is one such type of transformation and is also referred to as fixed data. It is necessary because it cannot be changed and if so will always consist of a finite set of data that is difficult to convert into the desired format due to high degree of redundancy. In cases where only some specific information needs to be encoded, the discrete data format is used. Data compression seeks to make the same information more available by reducing redundancy in the set of data.

Another artificial intelligence concept is called Information Norm or Domain Norm. This refers to the set of rules governing the behavior of the system when encountering different types of data. For example in the business domain, it may include the value of the product or service and its price range. The Domain Norm is a high amount of information may be stored in the system and/or in order to achieve the same accuracy required in the continuous data model.

Data mining in the context of information booth systems involves the process of finding, extracting and evaluating information that is pertinent to the customer interaction. Basically this means that the customer information is processed for the purpose of providing a better service and better products to the clients. During the information retrieval process, one can extract the information in an efficient manner. The information retrieved may comprise product information, technical details and other information that may help in making the decisions of the company.