Web Navigation Research Articles

Nepali Virtual AI Assistant

With the development of Artificial Intelligence (AI), much of our regular redundant work that does not require critical thinking is replaced by machines. The scope of the Internet of Things (IoT) is also increasing due to AI. IoT acts as a suitable platform for the application of AI in real life. In this paper, we present a Virtual AI Assistant that combines AI with IoT. Our system uses an ESP8266 (Node MCU) chip as the core microcontroller for the home automation application. It is an IoT-compatible microcontroller with a cloud connectivity feature that is accomplished with the help of WiFi (Wireless fidelity). This allows home appliances such as lights, fans, rice cookers, etc. to be controlled by desktop or mobile applications from any part of the world. Our system uses speech recognition as its primary source for controlling the application. The speech recognition feature can detect and distinguish people’s voices which is a handy feature in terms of security and privacy. Other than IoT, software features such as note-making, application initiators, web navigation, and automatic typing through speech recognition are also implemented in this system. Our work also makes use of the Nepali language for IoT applications for switching home appliances on and off. The AI model was trained from scratch manually for the Nepali language as proper audio datasets for the Nepali language are not available. Our work in the development of Nepali Virtual AI Assistant is to integrate hardware and software with AI to create user-friendly automation and ease in people’s daily lives.

Three-Dimensional Documentation and Virtual Web Navigation System for the Indoor and Outdoor Exploration of a Complex Cultural Heritage Site

Three-Dimensional Documentation and Virtual Web Navigation System for the Indoor and Outdoor Exploration of a Complex Cultural Heritage Site

Exploring Digital Competencies: Validation and Reliability of an Instrument for the Educational Community and for all Educational Stages

AbstractDigital competencies are very significant in terms of integrating digital resources into educational processes. This study presents the validity and reliability of an instrument created by Carrera et al. (2011), in order to evaluate the basic digital competence of the three main educational agents of the educational community (teachers, students, and parents) for all educational stages (Early Childhood Education, Primary Education, Secondary Education and Higher Education), making use of digital resources to (1) Skills in management and transfer of technological data, (2) Software and hardware skills, (3) Web navigation skills, (4) Skills in using word processors, (5) Data processing and management skills, y (6) Multimedia presentation design skills. The application of the instrument was carried out with a sample of 1,149 participants from all educational stages, coming from the entire territory of the Dominican Republic. Reliability was assessed using various measures, including Cronbach’s Alpha, Spearman-Brown Coefficient, Guttman’s Two Halves, McDonald’s Omega, and composite reliability. To validate the instrument, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were carried out with the purpose of understanding the validity and dimensionality of the scale (comprehension validity, construct validity, convergent, discriminant and invariance validity). The results demonstrated highly satisfactory reliability, and in terms of construct validity, a good fit of the model was observed, valid for any educational agent and for any educational stage. The final version of the instrument consists of 20 items classified into six latent factors.

SEO vs. UX in Web Design

This work addresses a research gap in digital marketing by attempting to compare the effort in achieving the best organic search engine ranking with the effort in providing the best user experience in web navigation. The objective is to validate companies' efforts in the digital world, and the study is focused on the toy sector in Spain, specifically on the Google search engine, measuring the user experience in web browsing through neuromarketing biometrics. The top 30 results for each Google search were collected for the 638 keywords related to toys in Spain. Subsequently, the three best-positioned websites for the Google search results were determined, and their user experience was measured using neuromarketing biometrics, triangulated with qualitative research. This approach allows for contrasting brand authority in the digital world (visibility in a search) with the user experience in navigation (trust and ease of purchase decision-making). Results indicate that the best-positioned websites do not necessarily correspond to the best web navigation experiences.

Individual differences in knowledge network navigation

With the rapid accumulation of online information, efficient web navigation has grown vital yet challenging. To create an easily navigable cyberspace catering to diverse demographics, understanding how people navigate differently is paramount. While previous research has unveiled individual differences in spatial navigation, such differences in knowledge space navigation remain sparse. To bridge this gap, we conducted an online experiment where participants played a navigation game on Wikipedia and completed personal information questionnaires. Our analysis shows that age negatively affects knowledge space navigation performance, while multilingualism enhances it. Under time pressure, participants’ performance improves across trials and males outperform females, an effect not observed in games without time pressure. In our experiment, successful route-finding is usually not related to abilities of innovative exploration of routes. Our results underline the importance of age, multilingualism and time constraint in the knowledge space navigation.

The influence of 360-degree VR videos on tourism web usage behaviour: the role of web navigability and visual interface design quality

Purpose Using the stimulus–organism–response (SOR) theoretical model, this empirical research aims to examine and validate how tourists’ interactions with 360-degree virtual reality (VR) videos incorporating Web navigability and visual interface design quality (stimulus) on travel websites can make tourists more engaged and then satisfied (organism), which could make them more likely to visit destinations and spread electronic word of mouth (e-WOM) (response). Design/methodology/approach Using the convenience sampling method, 975 responses were collected through a questionnaire. The data were analysed using Smart-PLS 4 software to investigate the hypothesised relationships. Findings The findings demonstrate that 360-degree VR videos significantly create Web user engagement, and Web user engagement is significantly associated with Web user satisfaction. The result shows that Web user engagement and satisfaction impact the intention to visit the tourist destination. Additionally, Web user satisfaction impacts e-WOM. Lastly, navigability and visual interface design quality are significantly moderated between 360-degree VR videos and Web user engagement. Research limitations/implications This research only examined the tourists’ behavioural intentions with 360-degree VR videos during the pre-travel phase. In contrast, future research may investigate how tourists behave with VR during the on-site and post-travel phases. Practical implications Tourism marketers should not only adopt 360-degree VR but also integrate Web navigability and visual interface design to boost Web users’ engagement on tourism websites. Originality/value This study advances the study of VR from the tourists’ psychological perspective. Moreover, the SOR theory has been re-examined from the VR and technology tourism perspectives. It provides a general understanding of the behavioural aspects of tourists in developing countries.

REVIEW OF MODELLING APPROACHES FOR WEBSITE-RELATED PREDICTIONS

This paper researches various modelling approaches for website-related predictions, offering an overview of the field. With the ever-expanding landscape of the World Wide Web, there is an increasing need for automated methods to categorize websites. This study examines an array of prediction tasks, including website categorization, web navigation prediction, malicious website detection, fake news website detection, phishing website detection, and evaluation of website aesthetics.

An Eye-tracking Study: Investigating the Impact of Website Theme Colors on Viewer Engagement

The Internet’s rapid evolution has transformed the media landscape, prompting brands and companies to transition from traditional print and TV to online media. Enhancing website design has become a focal point for effectively conveying information and capturing users’ attention. Among the various elements involved, the choice of web page theme color stands out as a crucial visual component in web navigation, significantly impacting the viewer’s user experience. Investigating the influence of web page colors on viewer attention is imperative. This study employs eye-tracking technology to delve into the impact of diverse web page colors on participants’ attention, particularly on news websites. An eye tracker was employed to meticulously record participants’ gaze patterns while browsing by experimenting with new pages featuring distinct theme colors. Data analysis revealed that red and blue colors garnered the most attention from viewers, followed by yellow, while gray-themed sites performed the least effectively in this regard. These findings offer valuable insights for web design improvement. In the context of news websites, red and blue are particularly effective in capturing and guiding people’s attention. When emphasizing or conveying breaking news, incorporating blue or red icons or relevant elements can be a powerful means of communication; however, it is equally important to be mindful of the potential for viewer visual fatigue when using highly saturated colors over a significant area. Therefore, designers must exercise care in determining the color balance when employing high-contrast and high-saturation hues.

CompTrails: comparing hypotheses across behavioral networks

AbstractThe term Behavioral Networks describes networks that contain relational information on human behavior. This ranges from social networks that contain friendships or cooperations between individuals, to navigational networks that contain geographical or web navigation, and many more. Understanding the forces driving behavior within these networks can be beneficial to improving the underlying network, for example, by generating new hyperlinks on websites, or by proposing new connections and friends on social networks. Previous approaches considered different hypotheses on a single network and evaluated which hypothesis fits best. These hypotheses can represent human intuition and expert opinions or be based on previous insights. In this work, we extend these approaches to enable the comparison of a single hypothesis between multiple networks. We unveil several issues of naive approaches that potentially impact comparisons and lead to undesired results. Based on these findings, we propose a framework with five flexible components that allow addressing specific analysis goals tailored to the application scenario. We show the benefits and limits of our approach by applying it to synthetic data and several real-world datasets, including web navigation, bibliometric navigation, and geographic navigation. Our work supports practitioners and researchers with the aim of understanding similarities and differences in human behavior between environments.

Chameleon: a cloud computing Industry 4.0 neutron spectrum unfolding code.

This work presents Chameleon, a cloud computing (CC) Industry 4.0 (I4) neutron spectrum unfolding code. The code was designed under the Python programming language, using Streamlit framework®, and it is executed on the cloud, as I4 CC technology through internet, by using mobile devices with internet connectivity and a web navigator. In its first version, as a proof of concept, the SPUNIT algorithm was implemented. The main functionalities and the preliminary tests performed to validate the code are presented. Chameleon solves the neutron spectrum unfolding problem and it is easy, friendly and intuitive. It can be applied with success in various workplaces. More validation tests are in progress. Future implementations will include improving the graphical user interface, inserting other algorithms, such as GRAVEL, MAXED and neural networks, and implementing an algorithm to estimate uncertainties in the calculated integral quantities.

A game-based augmented reality navigation system to support makerspace user education in a university library

PurposeA makerspace has recently been identified as an essential learning field for cultivating students’ creative and thinking abilities. Creating a makerspace service within a university library is vital, as it fosters innovation, interdisciplinary learning, practical skills, entrepreneurship and career readiness while transforming the library into a dynamic centre for hands-on education and collaboration. Nevertheless, the wide-ranging functions and uses of makerspace equipment can potentially lead to a situation where librarians are overwhelmed by their duties due to manpower constraints. Therefore, this study aims to develop a novel game-based augmented reality navigation system (GARNS) based on the Octalysis gamification framework and scaffolding theory to support makerspace user education, hoping to promote learners’ learning motivation and their immersive experience and to enhance the learning performance of makerspace user education.Design/methodology/approachWith a true experimental research method, 24 grade 11 students from a high school in Keelung City, Taiwan, were recruited to participate in the experiment on makerspace user education. Among them, ten students were randomly assigned to the experimental group using the GARNS and the other seven students were randomly assigned to a control group using the Web navigation system. The remaining seven students were assigned to a second control group using the narrative guided tour with a librarian to conduct makerspace user education.FindingsAnalytical results show that learners can achieve significant learning effectiveness using the GARNS, Web navigation system or traditional narrative guided tour with a librarian for makerspace user education. There were no significant differences in learning effectiveness and motivation neither between the GARNS group and the narrative guided tour with a librarian group nor between the Web navigation system group and the narrative guided tour with a librarian group. However, there were significant differences in learning effectiveness and motivation in terms of the value and expectation dimensions of learning motivation between the GARNS group and the Web navigation system group, and the GARNS group was significantly better than the Web navigation system group.Practical implicationsThe study’s practical implication on makerspace user education is to reduce the manpower of a university library with makerspace services by the proposed GARNS that can offer a practical solution to enhance the learning effectiveness and motivation of makerspace through immersive game-based autonomous learning. Additionally, the study’s theoretical contribution lies in its innovative combination of game-based learning and scaffolding theory, while its practical significance stems from its potential to revolutionize makerspace user education, enhance motivation and performance and influence the broader landscape of educational technology.Originality/valueThis study combines game-based learning with augmented reality tools to develop a novel GARNS, which provides an innovative and effective learning tool suitable for the characteristics of makerspace and contributes to promoting makerspace user education and diversified learning modes. Additionally, most interviewees believed that using GARNS for educating makerspace users could assist them in consistently evaluating, choosing and discovering educational tasks in a library makerspace. This study contributes to promoting the popularization of makerspace user education.

3D Data Integration for Web Fruition of Underground Archaeological Sites: A Web Navigation System for the Hypogeum of Crispia salvia (Marsala, Italy)

The diffuse data fruition of archaeological hypogeum sites still represents a challenge due to their limited accessibility and their preservation and maintenance issues. This implies that the fruition of these peculiar archaeological sites is often possible through digital reconstructions and interactive web navigation systems. The survey methodologies based on terrestrial laser scanning and photogrammetry allow making accurate and detailed digital reconstructions of these sites that are useful for virtual fruition purposes. In addition, many different systems can be used for remote web navigation and fruition. This work presents a possible solution for the virtual fruition of archaeological hypogea with a multiscale 3D web navigation system based on WebGL open-source technology. The system has been implemented for the Roman hypogeum of Crispia salvia, located in Marsala (southern Italy). The hypogeum belongs to the Archaeological Park of Lilibeo-Marsala and is considered one of the most important archaeological discoveries in this area for its extraordinary frescoes. Public accessibility of this site is limited because it is located outside the boundaries of the Archaeological Park, in the modern town, and covered by a residential building. In this case, the web navigation system adds an important contribution due to the limited real accessibility to the site. This work shows the framework for the construction of the web navigation system, where 3D surveys, digital reconstructions, 3D modeling, and web development are integrated. The choice of using an open-source technology for the web navigation system limits the costs of the process, and, at the same time, grants the web dissemination of site information.

Mining user's navigation structure by filtering impurity nodes for generating relevant predictions

Web Navigation Prediction (WNP) has been popularly used for finding future probable web pages. Obtaining relevant information from a large web is challenging, as its size is growing with every second. Web data may contain irrelevant noise, and thus cleaning such data is essential. In this paper, we emphasize the identification and elimination of noisy information from user-navigated web pages. The pruning of user browsed sessions by removing noisy webpages and their relations can help in the development of high-performing prediction models with fewer prediction errors. To minimize the prediction errors, we have proposed four pruning models namely PM3ER, PM3EN, PM3GI, and PM3EP which remove noisy web pages and their relations from the model consisting of varied simple and complex navigations. The study reveals that PM3ER is effective in prediction for websites with complicated structures resulting in complex navigations, and PM3EN is effective in predicting websites with a simple tree-like structure resulting in simple navigations. PM3ER has shown an improvement in predictions by up to 3% whereas PM3EN has attained improvement up to 5.45%.

Endometriosis in the time of internet: how web navigation affects women with endometriosis

Objectives Patients often search for health-related information on the internet allthough this trend may have some benefits, it also has some risks, such as misinformation. The aim of this study is to evaluate how Internet information seeking affect the level of anxiety in patients with endometriosis. Materials and methods This prospective observational study was conducted at our outpatient clinic between March 2019 and December 2020. We enrolled We enrolled all patients with a confirmed sonographic diagnosis of endometriosis who had sought information about the disease prior to our visit. We divided them into two groups based on the source of information (Internet only vs multiple sources). Before the visit, we asked women to fill-in validated questionnaires about anxiety, such as the Generalized Anxiety Disorder-7 (GAD) and the Spielberg State Trait Anxiety Inventory (STAI- Y6) and the Endometriosis Health Profile (EHP) − 5. After the visit, the STAI-Y6 was resubmitted to each woman. Results We enrolled 200 women who filled-in the questionnaires: 46 reported the Internet as the only source of information, 52 sought information also from medically qualified sources, 74 consulted only healthcare professionals, and 28 resorted to medical journals. Women who used the Internet as their exclusive source of information were younger on average and their STAI-Y6 score after the visit was significantly lower compared to other group (34.1 ± 11.5 vs 42.1 ± 14.7, p = .001). Moreover, the difference between the STAI-Y6 scores before and after our assessment was higher in these women (-18.3 ± 14.7 vs −10.3 ± 16.5, p = .003). Conclusions Women who sought information online were younger, had lower levels of state trait anxiety after our medical evaluation, and a had a greater reduction in anxiety levels after our examination compared to women who consulted other sources to learn more about endometriosis. KEY MESSAGES Women using only Internet are younger than those who use other sources of information. Women who researched symptoms online showed higher pre-examination anxiety levels. Patients with severe pain symptoms consulted both the internet and professionals.

Towards Digital Twinning on the Web: Heterogeneous 3D Data Fusion Based on Open-Source Structure

Recent advances in Computer Science and the spread of internet connection have allowed specialists to virtualize complex environments on the web and offer further information with realistic exploration experiences. At the same time, the fruition of complex geospatial datasets (point clouds, Building Information Modelling (BIM) models, 2D and 3D models) on the web is still a challenge, because usually it involves the usage of different proprietary software solutions, and the input data need further simplification for computational effort reduction. Moreover, integrating geospatial datasets acquired in different ways with various sensors remains a challenge. An interesting question, in that respect, is how to integrate 3D information in a 3D GIS (Geographic Information System) environment and manage different scales of information in the same application. Integrating a multiscale level of information is currently the first step when it comes to digital twinning. It is needed to properly manage complex urban datasets in digital twins related to the management of the buildings (cadastral management, prevention of natural and anthropogenic hazards, structure monitoring, etc.). Therefore, the current research shows the development of a freely accessible 3D Web navigation model based on open-source technology that allows the visualization of heterogeneous complex geospatial datasets in the same virtual environment. This solution employs JavaScript libraries based on WebGL technology. The model is accessible through web browsers and does not need software installation from the user side. The case study is the new building of the University of Twente—Faculty of Geo-Information (ITC), located in Enschede (the Netherlands). The developed solution allows switching between heterogeneous datasets (point clouds, BIM, 2D and 3D models) at different scales and visualization (indoor first-person navigation, outdoor navigation, urban navigation). This solution could be employed by governmental stakeholders or the private sector to remotely visualize complex datasets on the web in a unique visualization, and take decisions only based on open-source solutions. Furthermore, this system can incorporate underground data or real-time sensor data from the IoT (Internet of Things) for digital twinning tasks.

Validation of Individual Identification Through Decision Tree Packet Header Profiling

The drastic rise in the cybercrime rate associated with the surge of users' dependence on the Internet has elevated the concern of digital forensic examiners toward the footprints of perpetrators left in a virtual environment. However, suspect identification is a big challenge in network forensics due to the anonymous nature of data transmission across the network. This study utilises the decision tree classification approach to characterise users from their behavioural web navigation pattern using the meta-data of captured network packets (Destination IP, Protocol, Port Source, and Port Destination). A total of 95,795,379 network packet headers from 96 subjects were successfully collected. Their meta-data header packets were statistically profiled to generate digital fingerprints that try to link their action on the network to their identity accurately. Hence, CHAID decision tree modelling using Destination IP, Unique protocols, and a combination of the two, including Port source and Port destination, resulted in an accuracy of 4.07%, 6.34%, and 6.36%, respectively. However, the modelling could not create a reliable decision tree for the Port source and destination. The validation study on all the combined variables had a similar accuracy of 6.36%, indicating model created had reproducibility capability. Despite the outcome, the proposed method is not yet sufficiently strong for suspect identification. Further enhancement to improve its accuracy is required.

VALIDATION OF INDIVIDUAL IDENTIFICATION THROUGH DECISION TREE PACKET HEADER PROFILING

The drastic rise in the cybercrime rate associated with the surge of users' dependence on the Internet has elevated the concern of digital forensic examiners toward the footprints of perpetrators left in a virtual environment. However, suspect identification is a big challenge in network forensics due to the anonymous nature of data transmission across the network. This study utilises the decision tree classification approach to characterise users from their behavioural web navigation pattern using the meta-data of captured network packets (Destination IP, Protocol, Port Source, and Port Destination). A total of 95,795,379 network packet headers from 96 subjects were successfully collected. Their meta-data header packets were statistically profiled to generate digital fingerprints that try to link their action on the network to their identity accurately. Hence, CHAID decision tree modelling using Destination IP, Unique protocols, and a combination of the two, including Port source and Port destination, resulted in an accuracy of 4.07%, 6.34%, and 6.36%, respectively. However, the modelling could not create a reliable decision tree for the Port source and destination. The validation study on all the combined variables had a similar accuracy of 6.36%, indicating model created had reproducibility capability. Despite the outcome, the proposed method is not yet sufficiently strong for suspect identification. Further enhancement to improve its accuracy is required.

3D DATA INTEGRATION FOR WEB BASED OPEN SOURCE WebGL INTERACTIVE VISUALISATION

Abstract. Recent advances in open-source geospatial technologies in WebGIS allowed the visualization of a 3D complex environment on the web, exploiting realistic Globe reproduction of the real territorial asset. At the same time, in the field of gaming technologies, the new possibilities offered by open-source WebGL JavaScript libraries allowed the creation of Virtual Reality navigation models on the web. The integration between 3D GIS globe navigation models and VR environment navigation is a solution that offers a further level of detail in web navigation, exploiting the capabilities of web browsers in the best way. This research further contributes to this field, showing a workflow to integrate different 3D data in a VR and 3D WebGIS navigation model. The case study for this research is the new building of the University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC) of Enschede (The Netherlands). This work tests the online integration of variety of 3D input data that can lead to different Levels of Details (LoD) of the buildings inside the Globe-based WebGIS platform. The developed solution works on desktop and mobile devices using the capabilities of the most common web browsers, avoiding any software installation. The result of this work is based on completely open-source solutions that offers the possibility to navigate within a 3D model, which is useful for citizens, governmental or private institutions in decision-making processes. This work represents a first step towards the ambition to generate a web Digital Twin platform to combine datasets from different sources in a unique open-source solution.

색약자를 고려한 홈쇼핑 웹 네비게이션 컬러유니버설디자인의 배색에 관한 연구

In the digital information society, color blindness are forced to be the information disadvantaged group, and it's difficult for them to access the website information. Therefore, in this study analyzed coloring of web navigation using the CCA(color contrast analyser)program, a contrast ratio evaluation tool, considering color blindness, and proposed improvement solutions for major domestic home shopping. The results of the study showed that 5out of 7 home shopping stores used R-series colors, and 4 out of 5 home shopping stores used R-series colors did not meet meet the KWCAG standard. In the application of color, it is difficult to recognize not only for the ordinary people but also for the color blindness if a clear contrast of brightness is not applied. Therefore, it is recommended that the color of the text be reimbursed with Monsell 10 colors with a brightness contrast of 4.5:1 or more, and that the colors of the G, B, PB, P,and RP be applied to improve visibility together with the icon bar records, or that color schemes such as the outer line be used in the text. This measure will contribute to the construction of a color universal design color environment in which color weaknesses are not inconvenienced by the site's color scheme.

LaSER: Language-specific event recommendation

While societal events often impact people worldwide, a significant fraction of events has a local focus that primarily affects specific language communities. Examples include national elections, the development of the Coronavirus pandemic in different countries, and local film festivals such as the César Awards in France and the Moscow International Film Festival in Russia. However, existing entity recommendation approaches do not sufficiently address the language context of recommendation. This article introduces the novel task of language-specific event recommendation, which aims to recommend events relevant to the user query in the language-specific context. This task can support essential information retrieval activities, including web navigation and exploratory search, considering the language context of user information needs. We propose LaSER, a novel approach toward language-specific event recommendation. LaSER blends the language-specific latent representations (embeddings) of entities and events and spatio-temporal event features in a learning to rank model. This model is trained on publicly available Wikipedia Clickstream data. The results of our user study demonstrate that LaSER outperforms state-of-the-art recommendation baselines by up to 33 percentage points in MAP@5 concerning the language-specific relevance of recommended events.