Web Navigation Research Articles

A Bayesian Method for Comparing Hypotheses About Human Trails

When users interact with the Web today, they leave sequential digital trails on a massive scale. Examples of such human trails include Web navigation, sequences of online restaurant reviews, or online music play lists. Understanding the factors that drive the production of these trails can be useful, for example, for improving underlying network structures, predicting user clicks, or enhancing recommendations. In this work, we present a method called HypTrails for comparing a set of hypotheses about human trails on the Web, where hypotheses represent beliefs about transitions between states. Our method utilizes Markov chain models with Bayesian inference. The main idea is to incorporate hypotheses as informative Dirichlet priors and to calculate the evidence of the data under them. For eliciting Dirichlet priors from hypotheses, we present an adaption of the so-called (trial) roulette method, and to compare the relative plausibility of hypotheses, we employ Bayes factors. We demonstrate the general mechanics and applicability of HypTrails by performing experiments with (i) synthetic trails for which we control the mechanisms that have produced them and (ii) empirical trails stemming from different domains including Web site navigation, business reviews, and online music played. Our work expands the repertoire of methods available for studying human trails.

The role of digital identifier systems in the theory of digital objects

Theory of Digital Objects (TDO) can be considered as one of the important theories for explaining distinctive attributes and social practices of digital objects. The main aim of this study is to determine the role and position of digital identifiers and digital identifier systems in social practices of TDO. Results of applying comparative evaluation method demonstrated that the digital identifier systems can be considered as a third approach called identifiable Web, among memorable and navigable web in TDO. Moreover functions, technologically-induced tensions, challenges, counter mechanisms and emerging practices of the proposed approach had been investigated in contrast with the two existing social practices approaches. Results of this study could provide new ideas to administrators and researchers of these systems for promoting them from the sociotechnical aspect.

An Empirical Analysis of Web Navigation Prediction Techniques

With the advancement of Information Technology, web is growing rapidly and it has became necessary part of our daily lives. It is mandate to study the navigation behavior of the user to improve the quality of web site design for personalization and further recommendation. Analysis of web navigation behavior heavily relies on navigational models. This paper is an effort to give insights of current state-of-the-art techniques used for web navigation prediction. These navigation models are broadly classified into three categories: sequential mining, classification and clustering. Analytical analysis is performed on all the categories used in web navigation prediction. Further empirical analysis is performed on popular techniques of each category Markov Model (sequential mining), Support vector machine (classification) and K-means (clustering) on the common platform to measure the effectiveness of these techniques.

Website characteristics and web users' satisfaction in a higher learning institution

This paper aims to identify the characteristics of higher learning institution websites that will affect student satisfaction in Malaysian context. It develops one research model concerned with the determinants of higher learning institution website towards student satisfaction based on end-user computing instrument (EUCI) model. It was found that web presence, visual design and navigation design in higher learning institution website play a major role in creating satisfaction when using the website. This study contributes to academia as it tries to fulfil the gap in the area of higher learning institution website characteristics which is rather limited and unexplored in previous literature. The findings of this study can shed a light to higher learning website designer on factors or characteristics to focus on when designing the website. This research proves that findings on e-commerce website are also applicable in higher learning institution websites.

Bound of energy with real and complex roots of an intuitionistic fuzzy directed graph

We analyse the spreading rate of virus in terms of energy of an intuitionistic fuzzy graph by taking the website http://www.pantechsolutions.net/ of the web navigation of customers. Also, we derive the lower and the upper bounds for the energy of an intuitionistic fuzzy graph. Finally, we end up with the output results by taking the four periods of the given website.

The challenges of undergraduate online learning experienced by older workers in career transition

This paper presents the findings of a research project on older workers transitioning into work as vocational educators through online undergraduate university study. The study involved interpretive phenomenological analysis of the experiences of 10 older learners. Their experience of online learning was found to be shaped by diverse influences and to comprise three distinct but interrelated elements: their use of technology, their use of hypermedia and their independent learning. Challenges raised by each of these elements called for a distinctive response from the university, respectively: short-term, readily available technical advice and support; tutoring to develop Web navigation and exploration skills, or the provision of selected readings; and opportunities for online or face-to-face dialogical engagement with others. Recommendations for the online provision of higher education for such learners, then, pointed to the need for an appropriately distinctive response to challenges in each of the three elements: the use of technology calling for individualised and immediate responsiveness to learner issues; the use of hypermedia calling for aggregated advice and resources prepared in advance; and independent learning calling for the prior structuring of opportunities for interactive engagement. Further research is suggested focusing on the relative cost and effectiveness of different approaches to addressing those needs.

The Relationship Between Users’ Cognitive Styles and Their Navigation Behaviors on the World Wide Web

The purpose of this paper is to model users’ cognitive styles based on user web navigation patterns. The main aim is to investigate whether fuzzy clustering technique can group users in particular cognitive styles by means of psychometric test and navigation behavior analysis. Three navigation metrics are utilized to find identifiable groups of users that have similar navigation patterns in relation to their cognitive styles. Index of Learning questionnaire (ILS) is applied to extracting users’ cognitive styles. Users’ navigation behaviors are analyzed using a reproduced version of a brief introduction webpage of “Suishouji”.

Exploración de las posibilidades de la librería Three-js en proyectos de difusión del patrimonio cultural

<p>For whatever project related with the study and conservation of cultural heritage, the dissemination stage of tree-dimensional (3D) information must be a key part of the whole process. Most of the existing web-based platforms are using WebGL technology to disseminate 3D content through Web navigators, despite they are normally generic, with a low level of viewers ‘customization. Alternatively, users can make use of several libraries, most of them open source, which allow a complete adaptation to the specific project features, even though enough level of programming skills are necessary to use them. In the present paper we will describe the minimum requirements that any cultural heritage dissemination project should contain and its implementation using Three-js, one of the most versatile open source libraries for 3D visualization. In addition, we will show several examples of Three-js integration with other libraries that take advantage from HTML5 (HyperText Markup Language, version 5) to enhance the user's experience on a Web platform.</p>

LDQL: A query language for the Web of Linked Data

The Web of Linked Data is composed of tons of RDF documents interlinked to each other forming a huge repository of distributed semantic data. Effectively querying this distributed data source is an important open problem in the Semantic Web area. In this paper, we propose LDQL, a declarative language to query Linked Data on the Web. One of the novelties of LDQL is that it expresses separately (i) patterns that describe the expected query result, and (ii) Web navigation paths that select the data sources to be used for computing the result. We present a formal syntax and semantics, prove equivalence rules, and study the expressiveness of the language. In particular, we show that LDQL is strictly more expressive than all the query formalisms that have been proposed previously for Linked Data on the Web. We also study some computability issues regarding LDQL. We first prove that when considering the Web of Linked Data as a fully accessible graph, the evaluation problem for LDQL can be solved in polynomial time. Nevertheless, when the limited data access capabilities of Web clients are considered, the scenario changes drastically; there are LDQL queries for which a complete execution is not possible in practice. We formally study this issue and provide a sufficient syntactic condition to avoid this problem; queries satisfying this condition are ensured to have a procedure to be effectively evaluated over the Web of Linked Data.

Hypermedia navigation: Differences between spatial cognitive styles

Recently, many studies have investigated the role of individual and cognitive differences during Web navigation and Web searching. Despite this interest, no works have considered the role may assume individual differences in real-environment navigation during Web navigation. The aim of this work is to investigate the effect of different spatial cognitive styles: Landmark style (LS), Route style (RS) and Survey style (SS), on Web searching behaviour. In real-environment navigation, having a specific style determines the type of information individuals selected to navigate and orient themselves. We hypothesize that LS individuals are less proficient during Web exploration due to their analytical analysis of the environmental features. Vice versa SS individuals will show high performance on Web exploration for their holistic analysis of the World. We asked 30 College Students (10 LS, 10 RS, 10 SS) to solve three Web information tasks. The spatial cognitive style of participants was assessed through the Spatial Cognitive Style Test, and they were also asked to fill in a questionnaire about their internet and computer use. An ad hoc key-logger program for browsers was used to collect Web behaviour measures. In particular, the measures considered were: search engine tools used (e.g. back button), pages visited and revisited, time spent on information searching, and mouse cursor movements. The results showed significant differences between the spatial cognitive styles: LS seems to use a trial and error strategy in order to obtain the relevant information. Differences also emerged in the distribution of mouse cursor movements during Web navigation.

The modality effect on reading literacy: perspectives from students’ online reading habits, cognitive and metacognitive strategies, and web navigation skills across regions

ABSTRACTThis study tested the effects of the modality of reading formats (electronic vs. print), online reading habits (engagement in different online reading activities), use of cognitive strategies, metacognitive knowledge, and navigation skills on printed and electronic reading literacy across regions. Participants were 31,784 fifteen-year-old students (50.78% female) from 19 countries and economies in the 2009 Programme for International Student Assessment database. Results showed that students exhibited better reading literacy in the print environment. Moreover, information-seeking activities, control strategies, knowledge of metacognitive strategies, and navigation skills positively predicted reading literacy in both print and electronic formats for all regions, whereas social reading activities negatively predicted reading literacy in print and were most harmful for the Asian region in both formats. Memorization strategies were negatively associated with reading literacy in both formats for Australasian, Western and Eastern EU, and South American regions, but not for the Asian region. Online reading habits, regardless of types, had no impact on reading literacy in both formats for the South American region. The study findings provided suggestions for literacy instruction in the e-learning era across different regions.

Open plan offices as sociotechnical systems: What matters and to whom?

Open plan offices have proliferated for the past several decades with more and more workers being concentrated in office buildings. Several studies have identified a number of negative factors associated with open plan offices, and those include noise, speech interference, lack of privacy, and a perceived loss of control over work. While negative factors have been identified several times in the literature, many studies rely on either surveys or highly controlled environments. The objective of this study was to use a quasi-naturalistic environment based on a scaled world model to test three hypotheses of the impacts of office interference on editing and web navigation performance and mental workload. A mixed factor design was used that utilized continuous speech recordings, discontinuous speech recordings, and a quiet condition. Individual differences questionnaires were administered to measure focused attention, stress, and cognitive failures. After task completion, participants recorded mental workload ratings. Participants had higher performance accuracy in the document editing task across the speech interference conditions. Mental workload ratings were higher in the web navigation task in the discontinuous speech condition compared to the continuous speech condition. In contrast to the hypothesis, those reporting stronger focused attention performed more poorly across all speech conditions. Overall, the results were mixed. OPO work design must focus on individual differences among workers to determine how to customize design to facilitate performance.

Engaging customers during a website visit: a model of website customer engagement

Purpose A customer’s visit to a retail website is a critical “moment of truth” during which contemporary retailers attempt to simultaneously, during a single web navigation, capture customers’ attention, build rapport, and prompt them to act. By showing how to capture customer commitment over the course of a single website visit, the concept of customer website engagement, defined as “the process of developing cognitive, affective and behavioural commitment to an active relationship with the website”, addresses strategic concerns. Drawing from literature on engagement, the purpose of this paper is to consider how retail websites can engage customers during the course of a website navigation. A conceptual model of website customer engagement underpinned by relationship marketing and communication knowledge, shows how perceptions of the website’s exploration and sense-making potential can activate consumer engagement, and is then empirically tested. Design/methodology/approach Using survey data, measures of the four dimensions of engagement (interaction engagement, activity engagement, behavioural engagement, and communication engagement) and of three drivers are developed and validated. The model is tested empirically (n=301) using structural equation modelling. Findings The results support the process conceptualisation of engagement, which identifies organismic as well as conative stages, and show the distinct roles played by perceptions of informational exploration, experiential exploration and sense-making in activating engagement. Practical implications The study provides online retailing practice with an organising framework enabling online retailing managers to consider how, depending on their product category and their size, they might (re)design their website to optimally produce customer engagement. Originality/value The study contributes to online marketing and retailing knowledge by showing the relevance of the concept of engagement as it pertains to customers’ single navigations on retail websites, and by empirically showing, through a parsimonious model, how engagement can be activated and unfold.

Web Search Customization Approach Using Redundant Web Usage Data Association and Clustering

The massive growth of web consists of huge number of redundant information in related to some context. Due to which the need of information through a search provide high number of duplicate results which makes user to navigate number of sites to find the needed information. Users often miss their search pages when they browse the large and complex navigation of the web. Web customization is based on the use of the web logs can take advantage of the knowledge necessary to study the content and the structure of the internet to support. Searching information can be improvised in support of the implicit information generated by the web server in form logs for various web documents visited by users. This paper proposes a web search customization approach (WSCA) using redundant web usage data association and hierarchal clustering. Association generates a multilevel association for redundant data in the web navigation sites and clustering generates a cluster of frequent access patterns. The approach will improvise the real-time customization and also cost requirement for generating customized resources. The experiment evaluation shows an improvisation in precision rate in relevant to different queries against existing clustering approach..

Analysis of Web Visit Histories, Part I: Distance-Based Visualization of Sequence Rules

This paper constitutes Part I of the contribution to the analysis of web visit histories through a new methodological framework. Firstly, web usage and web structure mining are considered as an unique mining process to detect the latent structure of the web navigation across the web sections of a single portal. We extend association rules theory to web data defining new concepts of web (patterns) association and preference matrices, as well as of (indirect and direct) sequence rules. We identify the most significant rules, according to a multiple testing procedure. In the literature, web usage patterns can be visualized in no-distance-based graphs describing the navigation behavior across web pages with sequential arrows. In the following, we introduce a geometrical visualization of sequence rules at any click of the web navigation. In particular, we provide two distance-based visualization methods for the static analysis of all data tout court and the dynamic analysis to discover the most significant web paths click by click. A real world case study is considered throughout the methodological description.

“Modified Apriori Algorithm For Efficient Web Navigation Data Mining”

Web Data mining can be defined as knowledge discovery and analysis of useful information from the web. It is the process of determining user accessibility pattern, during the mining of log files and associated data from a particular Web site. Accurate web log mining results and efficient online navigational pattern prediction are undeniably crucial for tuning up websites and consequently helping in visitor’s retention. Like any other data mining task, web log mining starts with data cleaning and preparation and it ends up discovering some hidden knowledge which cannot be extracted using conventional methods. We are proposing an enhancement to the web log mining process and to the online navigational pattern prediction named Dynamic Apriori algorithm for mining both frequent and closed frequent item set over data stream in log file. The algorithm is appropriate for noticing latest or new changes in the set of frequent item set by modifying the traditional Apriori algorithm and Travelling Salesmen Problem (TSP) in the arriving data stream. The proposed modified algorithm we avoid unwanted and repetition of data. Here experimental analysis also use for improvement of web design, efficiently finding the User web navigation pattern which will help to grow the customer satisfaction and analysis.

Enhancing Web Navigation Appropriateness by Correlating Actual and Predictable Practice

a new method to identify navigation- related Web usability problems based on correlating Actual and Predictable usage patterns. The actual usage patterns can be extracted from Web server logs routinely recorded for operational websites by first processing the log data to identify users, user sessions, and user task-oriented transactions, and then applying an usage mining algorithm to discover patterns among actual usage paths. The anticipated usage, including information about both the path and time required for user-oriented tasks, is captured by our ideal user interactive path models constructed by cognitive ex- perts based on their cognition of user behavior. The comparison is performed via the mechanism of test oracle for checking results and identifying user navigation difficulties. The deviation data produced from this comparison can help us discover usability issues and suggest corrective actions to improve usability. A software tool was developed to automate a significant part of the activities involved. With an experiment on a small service-oriented website, we identified usability problems, which were cross-validated by do- main experts, and quantified usability improvement by the higher task success rate and lower time and effort for given tasks after suggested corrections were implemented. Index Terms—Cognitive user model, sessionization, software tool, test oracle, usability, usage pattern, Web server log.

Energy consumption and privacy in mobile Web browsing: Individual issues and connected solutions

Providing mechanisms to improve energy efficiency of mobile devices is, in the past few years, one of the important objectives in the field of green computing and energy savings. Several studies have addressed this issue from different point of views, i.e., hardware, software, as well as by analyzing the energy drained by different mobile applications. On the other hand, the energy consumption of Web browsing activities has been poorly addressed, given the lack of analysis about users’ real browsing sessions. In this paper we explore how energy savings in mobile devices can be effectively tackled by switching on/off filtering techniques offered by a privacy-enhancing technology. We present first, results about a survey that we conducted to understand the beliefs, attitudes, behaviors, and expectations of mobile users towards privacy and energy issues, and their behavioral intention on what kind of countermeasures adopt to reduce their privacy leakage. Then, we present a tool, mNoTrace, that allows to protect privacy during Web Navigation and prove, by an experimental study, that, by helping users in protecting their privacy, mNoTrace also achieves a significant reduction in terms of communication and computation overhead and thus battery consumption. Conclusions, remarks and lessons learned on our experimental methodology, that employs hardware-based instrumentation, real workloads, and testing on real sites, will conclude the paper.

Web navigation prediction using Markov-based models: an experimental study

Navigation prediction on web has gained a lot of importance due to its rapid growth. Web navigation prediction WNP deals with discovering the future pages for a particular website that users/the user may visit based on previously accessed web pages. WNP can be applied effectively in many applications such as web related search, latency reduction, improving website design, location prediction and personalised systems. Markov models and its variations are widely used to represent and analyse the navigational data on web. It can also used to predict user navigation behaviour. Diverse Markov model varies in terms of state-space complexity, prediction accuracy, model accuracy, coverage and failure cases. Research is still in progress for determining the suitability of Markov models for various web applications. Therefore, this paper presents a comparison of existing Markov-based models and its merit lies in the non-trivial conclusions derived by the experiments. Comparison is done in terms of state-space complexity, failure cases, coverage, prediction accuracy and model accuracy.

Webpage recommendation with web navigation prediction framework

Huge amount of user request data is generated in web-log. Predicting users' future requests based on previously visited pages is important for webpage recommendation, reduction of latency and online advertising. These applications compromise with prediction accuracy and modelling complexity. We propose a web navigation prediction framework for webpage recommendation WNPWR which creates and generates a classifier based on sessions as training examples. As sessions are used as training examples, they are created by calculating the average time on visiting webpages rather than traditional method which uses 30 minutes as default timeout. This paper uses standard benchmark datasets to analyse and compare our framework with two-tier prediction framework. Simulation results show that our generated classifier framework WNPWR outperforms two-tier prediction framework in prediction accuracy and time.