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Analytical CRM systems use techniques such as data mining, correlation, and pattern recognition to analyze customer data. These analytics help improve customer service by finding small problems which can be solved, perhaps by marketing to different parts of a consumer audience differently. [22] For example, through the analysis of a customer ...
Open Journal Systems (OJS) was conceived to facilitate the development of open access, peer-reviewed publishing, providing the technical infrastructure for the presentation of journal articles along with an editorial-management workflow, including article submission, peer-review, and indexing. OJS relies upon individuals fulfilling different ...
t. e. In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon. [ 1] Choosing informative, discriminating and independent features is a crucial element of effective algorithms in pattern recognition, classification and regression. Features are usually numeric, but structural ...
A semantic data model ( SDM) is a high-level semantics-based database description and structuring formalism ( database model) for databases. This database model is designed to capture more of the meaning of an application environment than is possible with contemporary database models. An SDM specification describes a database in terms of the ...
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A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision. The figure is an example of the interaction between process and data models.
The relational model ( RM) is an approach to managing data using a structure and language consistent with first-order predicate logic, first described in 1969 by English computer scientist Edgar F. Codd, [ 1][ 2] where all data is represented in terms of tuples, grouped into relations. A database organized in terms of the relational model is a ...
In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the 'outcome' or 'response' variable, or a 'label' in machine learning parlance) and one or more independent variables (often called 'predictors', 'covariates', 'explanatory variables' or ...