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Using Process Tracing to Analyze the Problem-Solving Process
Published in Karen L. McGraw, Karan Harbison, User-Centered Requirements: The Scenario-Based Engineering Process, 2020
Karen L. McGraw, Karan Harbison
Decision tables represent all the conditions that must be true for an action to be taken, rather than one condition at a time. A decision table is a matrix of rows and columns that depict conditions, actions, and decision rules that state what procedure to follow when certain conditions exist (Senn, 1989). Simple decision tables are comprised of conditions, actions, and notations that detail whether the action should be taken in each condition. Conditions include condition statements, which identify relevant conditions, and condition entries, which tell the value that applies for a particular condition. Actions include action statements, which list the set of steps that can be taken when a certain condition occurs, and entries, which show what specific actions in the set to take when a condition or combination of conditions are true.
ROUGH SET
Published in Kumar S. Ray, Soft Computing and Its Applications, Volume One, 2014
Rough set based data analysis starts from a data table called a decision table. The columns of the decision table are labeled by attributes and rows are labeled by objects of interest. The entries of the table are attribute values. Attributes of the decision table are divided into two disjoint groups called condition and decision attributes respectively. Each row of a decision table induces a decision rule, which specifies decision (action, results, outcome, and so on) if some conditions are satisfied. If a decision rule uniquely determines decision in terms of condition - the decision rule is certain. Otherwise the decision rule is uncertain. Decision rules are closely connected with approximations. Roughly speaking, certain decision rules describe lower approximation of decisions in theorems of conditions, whereas uncertain decision rules refer to the boundary region of decisions.
IT Systems Analysis and Design
Published in Sharon Yull, BTEC National for IT Practitioners: Core Units, 2009
The advantages of preparing a decision table are that all combinations of conditions will be considered and that there is a clear overview of what conditions have been met or not met. The standard layout also ensures that information is clearly understood and can be used by a number of end-users.
Estimation of raw silk quality using rough set theory
Published in The Journal of The Textile Institute, 2022
Niharendu Bikash Kar, Anindya Ghosh, Subhasis Das, Debamalya Banerjee
The decision table can be classified in two classes of attributes, called condition and decision attributes. Each row of a decision table determines a decision rule, which specifies decisions that should be taken when conditions pointed out by condition attributes are satisfied. Sometimes decision rules have the same conditions but different decisions. Such rules are called inconsistent (nondeterministic, conflicting), otherwise the rules are referred to as consistent (certain, deterministic, non-conflicting). Sometimes consistent decision rules are called sure rules, and inconsistent rules are called possible rules. Decision tables containing inconsistent decision rules are called inconsistent (nondeterministic, conflicting), otherwise the table is consistent (deterministic, non-conflicting).
Exploring the effect of group decision on information search behaviour in web-based collaborative GIS-MCDA
Published in Journal of Decision Systems, 2019
Mohammadreza Jelokhani-Niaraki
The information cells in the decision table contained the measured values of attributes associated with alternatives. Initially, the values of the information cells were hidden. In order to open and examine the information in a particular cell, the participant had to move the cursor into the cell and click on it. When a cell was opened, its value was immediately revealed and remains visible until the cursor is moved out of the cell. When the participant clicks on another cell, the information in the previous cell disappears and the new cell’s value comes into view. Hence, in this system, information was available in only one cell at a time. This feature allowed us to keep track of the order in which cells are opened, the amount of time and frequency that each cell is opened. Acquiring the decision information in the decision table allows decision makers to take into account their preferred range of attribute values (a particular range), least-preferred and most-preferred value for a given attribute, etc. during the specification of criteria preferences. Once the individual preferences were specified, the system computes and represents the alternative orderings (individual solution) on Google Maps.