JWE Abstracts 

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

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