An Anonymous Email Identification Solution based on Writing Structural Patterns

2015 ◽  
Vol 7 (2) ◽  
pp. 37-49
Author(s):  
Yanhua Liu ◽  
Guolong Chen ◽  
Yiyun Zhang
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Digital Forensics ◽  
Frequent Pattern ◽  
Analytic Hierarchy ◽  
Structural Pattern ◽  
Structural Patterns ◽  
Pattern Growth ◽  
Weight Calculation ◽  
Hierarchy Process

A method to analyze anonymous emails in digital forensics is presented in this paper. The frequent pattern-growth algorithm is used in the proposed method to analyze an email and obtain the structural email writing pattern of the user. The influence of a user's writing structural pattern on the analysis of an anonymous email varies. The analytic hierarchy process is used to calculate the weight of a user's different writing structural patterns. For a given anonymous email, matching the writing structural pattern and weight calculation can help investigators improve their decision making and determine the author of an anonymous email in forensic work.

On Moderate Fuzzy Analytic Hierarchy Process Pairwise Comparison Model With Subcriteria

2016 ◽  
Vol 2 (3) ◽  
pp. 54
Author(s):  
G. Marimuthu ◽  
G. Ramesh
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Fuzzy Ahp ◽  
Pairwise Comparison ◽  
Decision Models ◽  
Fuzzy Analytic Hierarchy Process ◽  
Analysis Method ◽  
Analytic Hierarchy ◽  
Comparison Model ◽  
Hierarchy Process

Decisions usually involve the getting the best solution, selecting the suitable experiments, most appropriate judgments, taking the quality results etc., using some techniques.  Every decision making can be considered as the choice from the set of alternatives based on a set of criteria.  The fuzzy analytic hierarchy process is a multi-criteria decision making and is dealing with decision making problems through pairwise comparisons mode [10].  The weight vectors from this comparison model are obtained by using extent analysis method.  This paper concern with an alternate method of finding the weight vectors from the original fuzzy AHP decision model (moderate fuzzy AHP model), that has the same rank as obtained in original fuzzy AHP and ideal fuzzy AHP decision models.

Study of Influence of Road Construction on Grassland in Inner Mongolia

2013 ◽  
Vol 807-809 ◽  
pp. 1881-1885
Author(s):  
Chun Mei Zhang ◽  
Min Zhao ◽  
Xue Lv
Keyword(s):  
Decision Making ◽  
Sustainable Development ◽  
Analytic Hierarchy Process ◽  
Inner Mongolia ◽  
Road Construction ◽  
Environment Protection ◽  
Analytic Hierarchy ◽  
The Sustainable Development ◽  
Inner Mongolia Grassland ◽  
Hierarchy Process

In this paper, the indexes that are used to assess the influence of road construction on Inner Mongolia grassland have been proposed based on the environment protection perspective. The Analytic hierarchy process was employed to evaluate the importance of different indexes regarding to influence. These indexes would be used to provide information for decision making about road construction in order to achieve the sustainable development of grassland.

JUDGMENT NUMBER REDUCTION: AN ISSUE IN THE ANALYTIC HIERARCHY PROCESS

2010 ◽  
Vol 09 (01) ◽  
pp. 175-189 ◽  
Author(s):  
LONG-TING WU ◽  
XIA CUI ◽  
RU-WEI DAI
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Pairwise Comparison ◽  
Random Variable ◽  
Analytic Hierarchy ◽  
Priority Vector ◽  
Judgment Error ◽  
Scale Error ◽  
The Analytic Hierarchy Process ◽  
Hierarchy Process

The Analytic Hierarchy Process (AHP) uses pairwise comparison to evaluate alternatives' advantages to a certain criterion. For decision-making problem with many different criteria and alternatives, pairwise comparison causes a prolonged decision-making period and rises fatigue in decision-makers' mentality. A question of practical value is if there exists a way to reduce judgment number and what influence the reduction will have on the overall evaluation of alternative ratings. To answer this question, we introduce scale error and judgment error into AHP judgment matrix. By expanding the scales defined in the AHP, scale error is eliminated. Taking judgment error as random variable, a new estimator to calculate priority vector is presented. In the end, an example is proved to show lowering judgment number will increase the probability of larger errors appearing in priority vector computation.

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