Rank-Order Weighting of Web Attributes for Website Evaluation
The rapid growth of web applications increases the need to evaluate web applications objectively. In the past few years some works like WebQEM has objectively evaluated the web applications. However, still weighting web attributes which is one step of evaluation of web applications is completely...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English |
| Published: |
2008
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/7131/1/FSKTM_2008_21a.pdf |
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| Summary: | The rapid growth of web applications increases the need to evaluate web applications
objectively. In the past few years some works like WebQEM has objectively
evaluated the web applications. However, still weighting web attributes which is one
step of evaluation of web applications is completely subjective, depending mostly on
experts’ judgments.
A two-step weighting approach is proposed to solve attribute weighting problem in
evaluating web applications in different domains. The approach divides the
weighting step into two steps which are ranking and then weighting. Firstly, the web
attributes are ranked according to the order of user expectations in web domains, and
secondly using rank-order weighting methods (Rank-sum weighting method (RS),
Reciprocal of the Ranks weighting method (RR), and Rank-Order Centroid
weighting method (ROC)) to elicit weight from the ranked attributes. A simulation is conducted to compare rank-order weighting methods (RR, RS, and
ROC) with the simulated experts. The experts’ judgments are simulated in the
simulation, assuming that for some particular web attributes, experts weight the
attributes completely subjective (randomly without prior ranking). Also for the
mentioned attributes, the proposed two-step weighting approach is used.
Two kinds of comparison are done; comparison on weights and comparison on
quality scores. Results from simulation are used in comparison to determine which
method (RR, RS, and ROC) can be a surrogate for experts’ judgments.
From the results of comparison, Rank-sum weighting method (RS) shows 90% of the
times completely comply with experts' judgements in terms of rank preservation
compared to RR and ROC. This shows that Rank-sum weighting method (RS) is the
best method. Rank-sum weighting method (RS) also has very small ValueLoss
compared to RR and ROC. From this, it can be said that, using RS weights will give
the particular web application a quality score that is not much difference from
experts’ judgments. Furthermore, 100% of times RS is the best method (compare to
RR and ROC) to conform to the experts in terms of choosing the best web
application quality. Thus, RS is suggested as a good surrogate for Experts’ weights
for the attributes when evaluating some web applications. |
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