Advances in Applied Technology, Computation and Artificial Intelligence to Improve the Web Ecosystem

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (20 June 2022) | Viewed by 20936

Special Issue Editors


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Guest Editor
Department of Information and Communication Engineering, University of Murcia, 28040 Madrid, Spain
Interests: learning analytics; games; technology-enhanced learning; computational social science; human-computer interaction
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Faculty of Computer Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
Interests: data privacy; database anonymization; differential privacy; privacy-enhancing technologies

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Guest Editor
Department of Network Engineering, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain
Interests: data privacy; cybersecurity; computer networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Since the appearance of the Web, many traditional businesses have been transformed: shopping, advertising, education, entertainment and more.  It has also been a platform for new markets such as the cloud, crowdsourcing, and social platforms. These previous and new environments are being rebuilt yet again during the era of big data, applying novel computational approaches and artificial intelligence. However, this ecosystem is still far from being mature and there are still controversial issues, such as finance models, security, and privacy that are fundamental for the sustainability and user experience of the ecosystem, while the technological developments keep advancing.

This Special Issue invites researchers to submit their work and advances that help build a more sustainable and user-friendly digital ecosystem. We welcome submissions that apply technology, computational approaches, or artificial intelligence in applications across the wide range of contexts within the Web, such as e-commerce, online advertising, social networks, entertainment or e-learning, amongst many others. The topics of interest include but are not limited to:

  • Literature reviews or surveys on the current trends and challenges of the Web ecosystem.
  • New technological developments that can represent an advance in the Web ecosystem.
  • Empirical research and case studies with detailed analyses that introduce innovation into the Web ecosystem.
  • Critical views or positioning papers on the privacy, security and ethics of the Web ecosystem.

 

Dr. José A. Ruipérez-Valiente
Dr. Javier Parra-Arnau
Dr. Jordi Forné
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Web Technologies
  • Artificial Intelligence
  • Human-Computer Interaction
  • Digital Economy
  • Online Advertising
  • Online Business
  • Privacy
  • Security
  • User Experience

Published Papers (8 papers)

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Editorial

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4 pages, 185 KiB  
Editorial
Technology, Computation and Artificial Intelligence to Improve the Web Ecosystem
by José A. Ruipérez-Valiente, Javier Parra-Arnau and Jordi Forné
Appl. Sci. 2022, 12(24), 12506; https://doi.org/10.3390/app122412506 - 07 Dec 2022
Viewed by 924
Abstract
Since the appearance of the Internet, many traditional businesses have been transformed, across the areas of shopping, advertising, education, entertainment, and more [...] Full article

Research

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12 pages, 252 KiB  
Article
Multidimensional Study on Users’ Evaluation of the KRAKEN Personal Data Sharing Platform
by Silvia Gabrielli, Silvia Rizzi, Oscar Mayora, Stefan More, Juan Carlos Pérez Baun and Wim Vandevelde
Appl. Sci. 2022, 12(7), 3270; https://doi.org/10.3390/app12073270 - 23 Mar 2022
Cited by 6 | Viewed by 1817
Abstract
Background: Recent advances in the design of blockchain-based personal data sharing platforms bring the benefit of empowering users with more control and privacy-preserving measures in sharing data products. However, so far very little is known about users’ intentions to adopt such platforms for [...] Read more.
Background: Recent advances in the design of blockchain-based personal data sharing platforms bring the benefit of empowering users with more control and privacy-preserving measures in sharing data products. However, so far very little is known about users’ intentions to adopt such platforms for providing or consuming data products. Objective: This study aims to investigate users’ main expectations, preferences, and concerns regarding the adoption of blockchain-based personal data sharing platforms in the health and education domains. Methods: Fifteen participants were involved in a multidimensional evaluation of a prototyped release of the KRAKEN blockchain-based data sharing platform and asked to assess it in the health or education pilot domains. Data collected during online group interviews with participants were analyzed by applying the micro interlocutor technique to provide a descriptive overview of participant responses. Results: Participants showed a marginal acceptance of the prototype usability, asking for some improvements of the user experience and for a more transparent presentation of the platform security and privacy preserving capabilities. Participants expressed interest in using the platform as data providers and consumers as well as setting privacy policies for sharing data products with third parties, including the possibility of revoking access to data. Conclusions: Blockchain-based data sharing platforms are more likely to engage target users when technical design is informed by a deeper knowledge of their needs, expectations, and relevant concerns. Full article
33 pages, 1533 KiB  
Article
Comprehensive Review and Future Research Directions on Dynamic Faceted Search
by Mohammed Najah Mahdi, Abdul Rahim Ahmad, Hayder Natiq, Mohammed Ahmed Subhi and Qais Saif Qassim
Appl. Sci. 2021, 11(17), 8113; https://doi.org/10.3390/app11178113 - 31 Aug 2021
Cited by 6 | Viewed by 3683
Abstract
In modern society, the increasing number of web search operations on various search engines has become ubiquitous due to the significant number of results presented to the users and the incompetent result-ranking mechanism in some domains, such as medical, law, and academia. As [...] Read more.
In modern society, the increasing number of web search operations on various search engines has become ubiquitous due to the significant number of results presented to the users and the incompetent result-ranking mechanism in some domains, such as medical, law, and academia. As a result, the user is overwhelmed with a large number of misranked or uncategorized search results. One of the most promising technologies to reduce the number of results and provide desirable information to the users is dynamic faceted filters. Therefore, this paper extensively reviews related research articles published in IEEE Xplore, Web of Science, and the ACM digital library. As a result, a total of 170 related research papers were considered and organized into five categories. The main contribution of this paper is to provide a detailed analysis of the faceted search’s fundamental attributes, as well as to demonstrate the motivation from the usage, concerns, challenges, and recommendations to enhance the use of the faceted approach among web search service providers. Full article
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28 pages, 15117 KiB  
Article
Optimizing the Frequency Capping: A Robust and Reliable Methodology to Define the Number of Ads to Maximize ROAS
by Jesús Romero Leguina, Ángel Cuevas Rumin and Rubén Cuevas Rumin
Appl. Sci. 2021, 11(15), 6688; https://doi.org/10.3390/app11156688 - 21 Jul 2021
Cited by 5 | Viewed by 3746
Abstract
The goal of digital marketing is to connect advertisers with users that are interested in their products. This means serving ads to users, and it could lead to a user receiving hundreds of impressions of the same ad. Consequently, advertisers can define a [...] Read more.
The goal of digital marketing is to connect advertisers with users that are interested in their products. This means serving ads to users, and it could lead to a user receiving hundreds of impressions of the same ad. Consequently, advertisers can define a maximum threshold to the number of impressions a user can receive, referred to as Frequency Cap. However, low frequency caps mean many users are not engaging with the advertiser. By contrast, with high frequency caps, users may receive many ads leading to annoyance and wasting budget. We build a robust and reliable methodology to define the number of ads that should be delivered to different users to maximize the ROAS and reduce the possibility that users get annoyed with the ads’ brand. The methodology uses a novel technique to find the optimal frequency capping based on the number of non-clicked impressions rather than the traditional number of received impressions. This methodology is validated using simulations and large-scale datasets obtained from real ad campaigns data. To sum up, our work proves that it is feasible to address the frequency capping optimization as a business problem, and we provide a framework that can be used to configure efficient frequency capping values. Full article
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16 pages, 17205 KiB  
Article
Advances in Search Strategy Using the Set of Brand Considerations in the Web Ecosystem
by Sungeun Kwon, Jonghyuk Kim and Zoonky Lee
Appl. Sci. 2021, 11(8), 3514; https://doi.org/10.3390/app11083514 - 14 Apr 2021
Cited by 1 | Viewed by 1521
Abstract
This study explores changes in a set of brand considerations as a result of web search strategies. Survey and personal computer log data of car buyers were used to identify online information search behavior for brands and products. Through this study, we found [...] Read more.
This study explores changes in a set of brand considerations as a result of web search strategies. Survey and personal computer log data of car buyers were used to identify online information search behavior for brands and products. Through this study, we found that higher frequencies of brand searching are associated with how much consumer-initiated sites and third-party-initiated sites are used, while lower frequencies of brand searching are only related to how much brand-initiated websites are used. We also concluded that ambivalent messages on consumer-initiated sites lead to the postponement of a decision and a continued search for another brand. In addition, third party-initiated information sources lower search costs, which lead to longer consumer journeys and expand the set of brands considered and searched. The results of this study can help marketers understand the importance of their own media and aid in the development of a digital media strategy. Full article
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22 pages, 2355 KiB  
Article
SENIOR: An Intelligent Web-Based Ecosystem to Predict High Blood Pressure Adverse Events Using Biomarkers and Environmental Data
by Sergio López Bernal, Javier Martínez Valverde, Alberto Huertas Celdrán and Gregorio Martínez Pérez
Appl. Sci. 2021, 11(6), 2506; https://doi.org/10.3390/app11062506 - 11 Mar 2021
Cited by 3 | Viewed by 1741
Abstract
Web platforms are gaining relevance in eHealth, where they ease the interaction between patients and clinician. However, some clinical fields, such as the cardiovascular one, still need more effort because cardiovascular diseases are the principal cause of death and medical resources expenditure worldwide. [...] Read more.
Web platforms are gaining relevance in eHealth, where they ease the interaction between patients and clinician. However, some clinical fields, such as the cardiovascular one, still need more effort because cardiovascular diseases are the principal cause of death and medical resources expenditure worldwide. The lack of daily control is the main reason hypertension is a current health problem, and medical web services could improve this situation. To face this challenge, this work proposes a novel intelligent web-based ecosystem, called SENIOR, capable of predicting adverse blood pressure events. The innovation of the SENIOR ecosystem relies on a wearable device measuring patient’s biomarkers such as blood pressure, a mobile application acquiring patient’s information, and a web platform consulting environmental services, processing data, and predicting blood pressure. The second contribution of this work is to consider novel environmental features based on the users’ location, such as climate and pollution data, to increase the knowledge about known variables affecting hypertension. Finally, our last contribution is a proof of concept with several machine learning algorithms predicting blood pressure values both in real-time and future temporal windows within one day has demonstrated the suitability of SENIOR. Full article
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11 pages, 720 KiB  
Article
Automatic Assessment of Privacy Policies under the GDPR
by David Sánchez, Alexandre Viejo and Montserrat Batet
Appl. Sci. 2021, 11(4), 1762; https://doi.org/10.3390/app11041762 - 17 Feb 2021
Cited by 12 | Viewed by 2832
Abstract
To comply with the EU General Data Protection Regulation (GDPR), companies managing personal data have been forced to review their privacy policies. However, privacy policies will not solve any problems as long as users do not read or are not able to understand [...] Read more.
To comply with the EU General Data Protection Regulation (GDPR), companies managing personal data have been forced to review their privacy policies. However, privacy policies will not solve any problems as long as users do not read or are not able to understand them. In order to assist users in both issues, we present a system that automatically assesses privacy policies. Our proposal quantifies the degree of policy compliance with respect to the data protection goals stated by the GPDR and presents clear and intuitive privacy scores to the user. In this way, users will become immediately aware of the risks associated with the services and their severity; this will empower them to take informed decisions when accepting (or not) the terms of a service. We leverage manual annotations and machine learning to train a model that automatically tags privacy policies according to their compliance (or not) with the data protection goals of the GDPR. In contrast with related works, we define clear annotation criteria consistent with the GDPR, and this enables us not only to provide aggregated scores, but also fine-grained ratings that help to understand the reasons of the assessment. The latter is aligned with the concept of explainable artificial intelligence. We have applied our method to the policies of 10 well-known internet services. Our scores are sound and consistent with the results reported in related works. Full article
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Review

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16 pages, 527 KiB  
Review
Application of the Extended Reality Technology for Teaching New Languages: A Systematic Review
by Noura Tegoan, Santoso Wibowo and Srimannarayana Grandhi
Appl. Sci. 2021, 11(23), 11360; https://doi.org/10.3390/app112311360 - 01 Dec 2021
Cited by 8 | Viewed by 3298
Abstract
Much attention has been given to the use of extended reality (XR) technology in educational institutions due to its flexibility, effectiveness, and attractiveness. However, there is a limited study of the application of XR technology for teaching and learning languages in schools. Thus, [...] Read more.
Much attention has been given to the use of extended reality (XR) technology in educational institutions due to its flexibility, effectiveness, and attractiveness. However, there is a limited study of the application of XR technology for teaching and learning languages in schools. Thus, this paper presents a systematic review to identify the potential benefits and challenges of using XR technology for teaching new languages. This review provides a basis for adopting XR technology for teaching languages in schools. This research also provides recommendations to successfully implement the XR technology and ways to improve motivation, engagement, and enhanced accessibility of learning and teaching resources on both students and teachers. To fulfil the aims of this research, previous studies from 2011 to 2021 are collected from various academic databases. This study finds that there is still a need to develop appropriate strategies for the development and implementation of XR technology for teaching new languages to school students. Full article
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