|
Vol.16 No.1&2 March 1, 2017
Research Articles
A Model-based Approach for Describing Offline
Navigation of Web Applications
(pp001-038)
Felix Albertos-Marco,
Victor M.R. Penichet, Jose Gallud, and Marco Winckler
The ubiquitousness of the Internet is changing the way users perform
their tasks. There is a trend and sometimes a real need to be always
connected. The client-server paradigm used in the Web greatly
facilitates the consumption of contents. However, there are many
situations where the user’s tasks in a Web application might be
interrupted due to an unexpected loss of connectivity, temporary
unavailability of Web servers, external events, etc., setting the browse
to an offline state. The availability of local storage in Web browsers
might suggest that users can perform some of their tasks when offline.
Nonetheless, several technical constraints might prevent users from
efficiently resuming their tasks over the Web after the offline period.
In this paper we present a model-based approach called the Offline
Model, which is aimed at supporting the execution of tasks interrupted
by loss of connectivity based on user navigation with Web applications.
Furthermore, we demonstrate how the Offline Model can be exploited to
mitigate some of the disruptive effects of interruptions, due to offline
navigation, on user tasks based on Web navigation in existent Web
applications. The feasibility of such a model approach is demonstrated
by a support tool and illustrated by a case study of navigation in a
real scenario: the DBLP Web site.
Association Link Network Based Semantic Coherence
Measurement for Short Texts of Web Events
(pp039-062)
Weidong Liu, Xiangfeng Luo, Junyu Xuan, Dandab
Jiang, and Zheng Xu
As novel web social Media emerges on
the web, large-scale short texts are springing up. Although these
massive short texts contain rich information, their disorder nature
makes users difficult to obtain the desired knowledge from them,
especially the semantic coherent knowledge. Different orders of these
short texts often express different semantic coherence states.
Therefore, how to automatically measure semantic coherence of short
texts is a fundamental and significant problem for web knowledge
services. Existing related works on the semantic coherence measurement
of different orders of short texts/sentences seldom focus on graph
structure of semantic link network for reflecting coherence change,
measuring coherence by these graph-based features and discovering some
interesting coherence patterns. In this paper, we propose an association
link network based semantic coherence measurement for short texts of web
events. Our method firstly construct an association link network from
which some graph-based features are then extracted to measure semantic
coherence of different orders and lastly some coherence patterns are
discovered for guiding automatically text ordering/generation. To
validate correctness of our method, we conduct a series of experiments
including sentence order permutation, sentence removal and
adding/replacing sentence and compare with other two methods. The
results show that our method can measure semantic coherence with higher
accuracy and outperforms other methods in some experiments. Such method
can be widely applied in web text automatic generation, web short text
organization and web event
summarization etc.
On the Value of Purpose-Orientation and Focus on
Locals in Recommending Leisure Activities
(pp063-074)
Beathice Valeri, Fabio Casati, and Florian
Daniel
Recommender
systems are omnipresent today, especially on the Web, and the quality of
their recommendations is crucial for user satisfaction. Unlike most
works on the topic, in this article we do not focus on the algorithmic
side of the problem (i.e., searching for the algorithm that better
learns from the collected user feedback) and instead study the
importance of the data in input to the algorithms, identifying the
information that should be collected from users to build better
recommendations. We study restaurant recommendations for locals and show
that fine-tuned data and state-of-the-art algorithms can outperform the
leading recommendation service,
TripAdvisor.
The findings make a case for better-thought and purpose-tailored data
collection techniques.
An approach for building Mobile Web Applications
through Web Augmentation
(pp075-102)
Gabriela A. Bosetti, Sergio Firmenich, Silvia
E. Gordillo and Gustavo Rossi
Mobile Web Applications combine traditional navigation access
enriched with location-based services, which results in a more complex
development process since there are a myriad of issues to consider while
integrating these kinds of behaviours. This complexity increases even
more if the integration of another specific functionality is considered,
as personalization or context-aware services. In this article we present
a novel approach to facilitate the development of Web applications that
enhance existing ones with mobile features through client-side Web
Augmentation. Assuming the existence of a set of Web pages that could be
associated to a physical object and some mechanism for location sensing,
we allow developers to define mobile services or adaptations according
to their own interests. We present a detailed comparative analysis of
the features we provide against other similar approaches, in order to
clearly highlight those aspects that distinguish our work from existing
ones. Finally, we show that this approach is feasible and effective by
presenting two prototype applications for two possible scenarios and the
results of our first experiment.
Constraint-based Context Modeling and Management
for Personalized Mobile Systems
(pp103-125)
Javad Berri
The capability of adapting to environmental changes and fulfilling
specific needs of nomadic users empowers mobile devices with new
value-added features. Users on the move are expecting real time and
personalized services that are adjusted to their needs and that fit
within their current time and space settings. Context-aware systems are
distinguished by: i) their ability to profile users; ii) their awareness
about device capabilities; and iii) their environmental knowledge. The
availability of wireless networks supports context-aware systems through
ubiquitous sensors and web services used to gather contextual
information in order to offer users exceptional interactive experiences.
In order to cope with information overload, collected data on the
changing environmental context needs efficient management. In this
research, we present a constraint-based context management system which
handles efficiently complex situations in adopting a desired behaviour
whenever a specific change occurs in the environment. This is
accomplished through a set of knowledge-based rules which validate the
consistency of the context by monitoring system constraints to trigger
automatic context updates. We evaluate our dynamic context-consideration
approach through real-life scenarios while comparing three
consistency-validation strategies.
An Automated Web Page Classifier and an Algorithm
for the Extraction of Navigational Pattern from the Web Data
(pp126-144)
Abdul R.W. Sait and T. Meryyappan
There is a demand for web intelligence in e-business and internet
oriented markets. Many data crunching tools are available for the
vendors to predict the customer behaviour on their website; still, there
is a vacuum exist, and they fail to grab visitor attention on their
products. Internet crimes are increasing exponentially with the growth
of popularity of the internet. Web page classification (WPC) is a
technique to classify the web page into a particular category by using
its content and attributes like URL, Meta, and Title tags.
Classification of web pages provides an option for an organization/
University to either block or allow a web page to the employees /
students. Weblog pattern (WLP) mining is a favourite tool to extract
useful patterns and deduce knowledge for the development of the website.
The proposed work found the solutions for the extraction of WLP and WPC.
The work has executed neural fitted Q-Iteration (NFQ) [1] method to
classify Tamil and English web pages and extract the types of visitor
visits the web page using a weblog. The experiment results show that
there are an economic time and memory usage of the proposed method and
improved percentage of accuracy comparing to existing methods.
Verifying Soundness of Geodata Web Service
Composition Based on Petri Nets
(pp145-160)
N. Xu, S-P Peng, and Z-G Wang
The emergence of service-oriented architecture (SOA) has made it
possible to establish easily accessible geodata web services and perform
distributed geodata processing and modelling, which facilitate the
provision of geo information in real time. Composition is an important
method for dynamically combining distributed individual services and can
be incorporated into geoprocessing workflows. Business Process Execution
Language (BPEL) and service specifications provided by the Open
Geospatial Consortium (OGC) have become the industrial standards for
executing geodata web service composition. However, current geodata web
service composition soundness verification is beyond the capabilities of
BPEL. Soundness verification in the design process can facilitate
efficient and cost-effective geodata web service composition execution.
To address this issue, Petri nets were used in this study for geodata
web service composition analysis. A geodata web service was modelled
based on a service net using Petri nets. The geodata web service
composition was modelled based on the composition structure. The
soundness properties of the geodata web service composition, such as
reachability, boundedness, and deadlock, were also analysed. The
proposed approach was shown to provide compliant support for geodata web
service composition.
Mixed-Opinion Classification of Web Forum Posts using Lexical and
Non-Lexical Features
(pp161-176)
Hikmat Ullah Khan
Back
to JWE Online Front Page
|
