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Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...
The user, rather than the database itself, typically initiates data curation and maintains metadata. [8] According to the University of Illinois' Graduate School of Library and Information Science, "Data curation is the active and on-going management of data through its lifecycle of interest and usefulness to scholarship, science, and education; curation activities enable data discovery and ...
Data should be consistent between different but related data records (e.g. the same individual might have different birthdates in different records or datasets). Where possible and economic, data should be verified against an authoritative source (e.g. business information is referenced against a D&B database to ensure accuracy).
It exists, however, in many variations on this theme, such as the Cross-industry standard process for data mining (CRISP-DM) which defines six phases: Business understanding; Data understanding; Data preparation; Modeling; Evaluation; Deployment; or a simplified process such as (1) Pre-processing, (2) Data Mining, and (3) Results Validation.
Data processing is the collection and manipulation of digital data to produce meaningful information. [1] Data processing is a form of information processing , which is the modification (processing) of information in any manner detectable by an observer.
Most preprocessors are specific to a particular data processing task (e.g., compiling the C language). A preprocessor may be promoted as being general purpose, meaning that it is not aimed at a specific usage or programming language, and is intended to be used for a wide variety of text processing tasks.
Understanding the differences between quantitative data vs. qualitative data, as well as formative assessment vs. summative assessment that tease out this data can be defined as assessment literacy. [5] Building assessment literacy also includes knowing when to use which type of assessment and the resulting data to use to inform instruction.
Preprocessing can refer to the following topics in computer science: Preprocessor , a program that processes its input data to produce output that is used as input to another program like a compiler Data pre-processing , used in machine learning and data mining to make input data easier to work with