Vol.11 No.1 March 1, 2012
A Framework for Interactively Helpful Web Forms
Morten Bohoj, Niels Olof Bouvin, and Henrik Gammelmark
AdapForms is a framework for adaptive forms, consisting of a form
definition language designating structure and constraints upon
acceptable input, and a software architecture that continuously
validates and adapts the form presented to the user. The validation is
performed server-side, which enables the use of complex business logic
without duplicate code. Thus, the state of the form is kept persistently
at the server, and the system ensures that all submitted forms are valid
and type safe.
Domain Specific Language for the Generation of Learning Management
Carlos E. Montenegro-Marin, Juan M.
Cueva-Lovelle, Oscar Sanjuan-Martinez and
Nowadays there are many research projects conducted
in the areas of Learning Management Systems (LMS) and Model-Driven
Engineering (MDE). These research projects have shown that there are LMS
platforms with different architectures and inoperative to each other.
The most significant contribution of MDE has been the creation of a
common meta-metamodel. This meta-metamodel allows transformations
between different models. This research work presents a LMS metamodel.
The metamodel created is based on the study of five LMS platforms. The
LMS metamodel is a global model that makes a bridge for the
transformation of modules between the model and different LMS platforms,
and it also presents the development of a Domain Specific Language (DSL)
tool to validate the metamodel, the transformation process of the model
with our DSL Tool to modules deployed in Moodle, Claroline and Atutor,
and finally testing and validation of creating modules with LMS
platforms VS creating modules with our DSL Tool.
A Feature-Opinion Extraction Approach to Opinion Mining
Bolanle A. Ojokoh and Olumide Kayode
With the rapid expansion of the web and
e-commerce in recent times, increasingly numerous products are bought
and sold on the Web. A lot of product reviews which would be very useful
for potential customers to make better decisions are generated by web
users. It is highly essential to produce a correct and quick summary of
these reviews. In this paper, we propose a method that extracts feature
and opinion pairs from online reviews, determines the polarity and
strength of these opinions with the aim of summarizing and determining
the recommendation status of the customers’ reviews. The evaluation
results on opinion extraction from the reviews of digital camera
demonstrate the effectiveness of the proposed technique.
Prediction Algorithms for Prefetching in the Current Web
Josep Domenech, Julio Sahuquillo, Jose A. Gil, and Ana Pont
This paper reviews a representative subset of the prediction
algorithms used for Web prefetching
classifying them according to the information gathered. Then, the DDG
algorithm is described. The main novelty of this algorithm lies in the
fact that, unlike previous algorithms, it creates a prediction model
according to the structure of the current web. To this end, the
algorithm distinguishes between container objects and embedded objects.
Its performance is compared against important existing algorithms, and
results show that, for the same amount of extra requests to the server,
DDG always outperforms those algorithms by reducing the perceived
latency up to 70% more without increasing the complexity order.
Predictive Self-Healing of Web Services Using
Mohsen Sharifi, Somayeh Bakhtiari Ramezani, and Amin Amirlatifi
Existing self-healing mechanisms for Web services
constantly monitor services and their computational environment, analyze
system state, determine failure occurrences, and execute built-in
recovery plans (MAPE loop). We propose a more pro-active self healing
mechanism that uses a multi-layer perceptron ANN and a health score
mechanism to learn about the occurrences of failures or quality of
service degradation in advance, without requiring modifications to the
framework of services used by applications. Highest score is assigned to
the system upon start and is degraded during system execution whenever a
service fails to operate or the time-to-leave (TTL) of the client side
requests increases. Application of the proposed mechanism to a set of
vehicle tracking Web services decreased the probability of out of
service occurrences by 70% and increased system quality of service by
13%. The overhead of the mechanism was nearly 3% and negligible, whilst
TTL for a request from the client side decreased by 20%.
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