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Vol.17 No.3&4 June 1, 2018
Web
Engineering Technologies in the Era of BigData
Editorial
(pp181-182)
Francisco José
Domínguez-Mayo, Julián Alberto García-García,
and
Laura García-Borgoñón
Challenges for the Adoption of Model-Driven Web
Engineering Approaches in Industry
(pp183-205)
Esteban Robles Luna, Juan Miguel Sánchez-Begines, Jose Matías Rivero,
Leticia Morales-Trujillo,
Jose G. Enríquez, and Gustavo Rossi
Model-Driven Web Engineering
approaches have become an attractive research and technology solution
for Web application development. However, for more than 20 years of
development, the industry has not adopted them due to the mismatch
between technical versus research requirements. In the context of this
joint work between academia and industry, the authors conduct a survey
among hundreds of engineers from different companies around the world
and, by statistical analysis, they present the current problems of these
approaches in scale. Then, a set of guidelines is provided to improve
Model-Driven Web Engineering approaches in order to make them viable
industry solutions.
MARIA: A Process to Model Entity Reconciliation
Problems
(pp206-223
J.G. Enríquez, M. Olivero, A.
Jimenez-Ramirez, M.J.
Escalona, and M. Mejías
Within the development of software systems, the development of web
applications may be one of the most widespread at present due to the
great number of advantages they provide such as: multiplatform, speed of
access or the not requiring extremely powerful hardware among others.
The fact that so many web applications are being developed, makes
enormous the volume of information that it is generated daily. In the
management of all this information, the entity reconciliation (ER)
problem occurs, which is to identify objects referring to the same
real-world entity. This paper proposes to give a solution to this
problem through a web perspective based on the Model-Driven Engineering
paradigm. To this end, the Navigational Development Techniques (NDT)
methodology, that provides a formal and complete set of processes that
bring support to the software lifecycle management, has been taken as a
reference and it has been extended adding new activities, artefacts and
documents to cover the ER. All these elements are defined by a process
named Model-Driven Entity ReconcilIAtion (MaRIA), that can be integrated
in any software development methodology and allows one to define the ER
problem from the early stages of the development. In addition, this
proposal has been validated in a real-world case study helping companies
to reduce costs when a software product that must give a solution to an
ER problem has to be developed.
An Approach for
Guesstimating the Deployment Cost in Cloud Infrastructures at Design
Phase in Web Engineering
(pp224-240)
J.C. Preciado, R.
Rodríguez-Echeverría,
J.M. Conejero, F. Sánchez-Figueroa
and A.E. Prieto
Nowadays, the total cost of cloud computing
infrastructures for Web applications is calculated in deployment and
production phases. Recently, the scientific community offers several
methodologies to calculate the most suitable infrastructure at these
stages to minimize its monetary costs while covering Service Level
Agreement (SLA) constraints. On the other hand, Model Driven Web
Engineering is taking advantages of code generation from Design level.
With both concepts in the scene, in this work we show the first stage
toward an approach to estimate the production costs in cloud computing
infrastructures at Design phase, choosing the right infrastructure for
the job. The process we have performed started defining the variables of
the analysis, measuring the time needed in each different combination
obtained, validating the confidence of results obtained and finally
applying them to an illustrative example to exemplify the proposal in
practical terms.
Other Research Articles
OntoNavShop:
An Ontology-Based Approach for Web-Shop Navigation
(pp241-269)
Philip Ruijgrok, Flavius Frasincar, Damir Vandic,
and Frederik Hogenboom
Existing literature shows that navigation and visualization features
play a significant role in successful Web shop design. Traditional Web
shops, however, often lack a uniform, intuitive interface to navigate
through products, while also providing an insightful overview of the
product assortment. In this article, we employ
ontologies
for the presentation of product assortments in Web shops in order to
ease the users' process of finding their desired products.
OntoNavShop
visualizes the product assortment ontology directly in a Web browser
using a circular view algorithm that outputs
SVG
graphics. Consumers can navigate uniformly through the ontology and zoom
into its categories. The
visualisation
is evaluated on efficiency, user satisfaction, and specific problems
against a classical tree-based Web shop. Our evaluations under a
representative group of users show that users maintain a better overview
of the structure of the product assortment, while being able to find
products more quickly (i.e., less time) and more efficiently (i.e., less
clicks) than in our benchmark Web shop. The participants prefer the
OntoNavShop over the classical
approach, and the identified problems are rather minor.
Hidden Webpages
Detection Using Distributed Learning Automata
(pp270-283)
Manish Kumar
and Rajesh Bhatia
Webpages directly connected to each
other on the Web can be reached easily by following hyperlinks. Those
webpages that are not linked by hyperlinks comprises hidden Web and it
is challenging to find them. Furthermore, most of webpages in hidden Web
are generated dynamically. This paper proposes first time an algorithm
to find webpages in hidden Web using distributed learning automata.
Learning automata use its self-learning characteristic of taking action
based on the action probabilities using <keyword-value> pairs. These
actions may lead the current webpage to hidden webpages that are
generated dynamically. At each stage of the proposed algorithm, we
determine the edge that should be chosen to reach webpage of interest.
The proposed algorithm is validated on four different websites from
dmoz.org. Precision-recall curve and coverage plot in the results
section shows the effectiveness of the proposed algorithm.
Implementation and
Evaluation of a Resource-based Learning Recommender based on
Learning Style and Web
Page Features
(pp284-304)
Mohammad Tahmasebi,
Faranak F. Ghazvini, and Mahdi Esmaeili
It is generally believed that recommender systems are a suitable key to
overcome the information overload problem. In recent years, a special
research area in this domain has emerged that concerns recommender
systems for Technology Enhanced Learning, in particular, self-regulated
learning with resources on the web, known as Resource-Based Learning.
Grey-sheep users are a major challenge in RecsysTEL. This group of users
have completely different opinions from other users. They do not profit
from collaborative algorithms,
so they must be supported in discovering learning resources relevant to
their characteristics and needs. The main contribution of this work is
to develop a feature-based educational recommender system which
interacts with the user based on his or her learning style. The learning
style dimensions would be determined based on Felder-Silverman theory.
In addition, the system crawls and extracts the necessary meta-data of
sample OCW’s web pages. Based on the proposed web page ranking formula,
the user’s learning style dimension and web page feature’s vector would
be accommodated to generate learning object suggestions. The general
satisfaction, perception and motivation towards the proposed method
measured among 77 science and engineering students by a questionnaire.
Moreover, the system has been
evaluated to
provide feedbacks on its suitability.
The research findings imply
that the proposed method outperforms the general search
algorithm. This system can
be used as a template in formal and informal learning and
educational environments as a RecsysTEL.
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