Implicit measures of lostness and success in web navigation

In two studies, we investigated the ability of a variety of structural and temporal measures computed from a web navigation path to predict lostness and task success. The user’s task was to find requested target information on specified websites. The web navigation measures were based on counts of visits to web pages and other statistical properties of the web usage graph (such as compactness, stratum, and similarity to the optimal path). Subjective lostness was best predicted by similarity to the optimal path and time on task. The best overall predictor of success on individual tasks was similarity to the optimal path, but other predictors were sometimes superior depending on the particular web navigation task. These measures can be used to diagnose user navigational problems and to help identify problems in website design.     

Evaluation of the usability of digital maintenance manuals developed without either user input or a task analysis

The primary objective was to investigate the value that can be added to a low-cost digital maintenance manual by the addition of a navigational aid. Two versions of a digital maintenance manual were developed, the difference between them being the number of design heuristics observed when designing navigational aids. Neither version was based on an analysis of the tasks carried out by users, nor were users involved in the design process. Instead, the manuals were developed directly from the digital information used to produce the existing paper manual. Usability trials were carried out to test both versions according to the time taken and errors committed by users during typical information retrieval tasks. Users were questioned to determine their ease of use (EOU) perceptions for each manual. The main outcomes were that the navigation aid used in the second version reduced the time taken to use the manual but increased the number of errors made by users. The navigational aid also seemed to reduce the perceived EOU compared with the first version. In both cases, the perceived EOU was lower than for a previous digital manual that had been developed using a task analysis and user input. The paper concludes by recommending the development of a generic task model of user interaction with digital maintenance manuals.     

Navigation in 3D virtual environments: Effects of user experience and location-pointing navigation aids

In this paper, we describe the results of an experimental study whose objective was twofold: (1) comparing three navigation aids that help users perform wayfinding tasks in desktop virtual environments (VEs) by pointing out the location of objects or places; (2) evaluating the effects of user experience with 3D desktop VEs on their effectiveness with the considered navigation aids. In particular, we compared navigation performance (in terms of total time to complete an informed search task) of 48 users divided into two groups: subjects in one group had experience in navigating 3D VEs while subjects in the other group did not. The experiment comprised four conditions that differed for the navigation aid that was employed. The first and the second condition, respectively, exploited 3D and 2D arrows to point towards objects that users had to reach; in the third condition, a radar metaphor was employed to show the location of objects in the VE; the fourth condition was a control condition with no location-pointing navigation aid available. The search task was performed both in a VE representing an outdoor geographic area and in an abstract VE that did not resemble any familiar environment. For each VE, users were also asked to order the four conditions according to their preference. Results show that the navigation aid based on 3D arrows outperformed (both in terms of user performance and user preference) the others, except in the case when it was used by experienced users in the geographic VE. In that case, it was as effective as the others. Finally, in the geographic VE, experienced users took significantly less time than inexperienced users to perform the informed search, while in the abstract VE the difference was significant only in the control and the radar conditions. From a more general perspective, our study highlights the need to take into specific consideration user experience in navigating VEs when designing navigation aids and evaluating their effectiveness.     

基于蚁群行为的动态挖掘用户导航模式兴趣模型

随着电子商务的快速发展,一个越来越重要的问题是如何挖掘并预测用户的导航模式。挖掘用户的导航模式是Web使用挖掘的一项重要任务,也是产生导航推荐的基本方法。由于用户的兴趣是不断变化的,因此很难准确跟踪用户的导航模式。在提出了一种蚁群模型来解决该问题。把Web用户看成是人工的蚂蚁,然后应用蚂蚁理论来指导用户在网站上的选择。首先,基于Web日志数据建立一个用户导航模型;其次,设计了一个算法,动态挖掘群体用户偏好的导航模式;最后,对真实数据集的实验结果表明该方法是有效的。     

Interacting with hypertext: an experimental investigation of navigation tools

The functionality that comes from hypertext has been an important driver in the growth of electronic commerce. The appropriate use of navigation tools and design of Web sites remains, however, an open research question. The objective of this study was to compare the impact of alternative navigation tools on users’ productivity differences in the retrieving of information. The selected navigation tools are: hierarchical design both with and without page hyperlinks, sequential both with and without page hyperlinks and a search engine. A laboratory experiment tested the effect of these navigation tools. A total of 430 subjects were randomly assigned to work with one of the five navigation tools. The productivity outcomes of the subjects were measured in terms of performance on the information retrieval task, search efficiency, and the self-perception of productivity. The task was an information search of medium complexity. An analysis of the results identifies navigation tools to be a contributing factor to users’ productivity.     

How to Overcome Disorientation in Mobile Phone Menus: A Comparison of Two Different Types of Navigation Aids

The current study was concerned with the basic question of how to overcome users' disorientation when navigating through hierarchical menus in small-screen technical devices, as for example mobile phones. In these devices, menu functions are typically organized in a tree structure. Two different navigation aids were implemented into a computer simulation of a real mobile phone (Siemens S45®). The interface of the first navigation aid (the "category" aid) showed the name of the current category as well as a list of its contents. The interface of the other navigation aid (the "tree" aid) was identical to the first except that it also showed the parents and parent–parents of the current of the category and it indented the subcategories to emphasize the hierarchical structure. For the study, 16 younger (23–28 years) and 16 older adults (46–60 years) had to solve 9 common phone tasks twice consecutively to measure learnability. To gain further insight into user characteristics modulating navigation performance and possibly interacting with the utility of the navigation aids, we assessed users' verbal memory and spatial abilities. Dependent variables were task effectiveness (number of tasks solved) and efficiency (time on task, number of returns in menu hierarchy, and returns to the top). The results reveal a consistent and significant advantage of the tree aid for both age groups, an advantage that was larger for users with lower spatial abilities and older adults. In general, older adults had lower verbal memory and spatial abilities, which were found to account for their lower navigation performance. We assume that the strong advantage of the tree aid is due to the spatial information on the menu structure, which thus conveys survey knowledge. This allows users to form an adequate mental representation of the menu. It is recommended to add a navigation aid providing survey knowledge into the displays of small-screen devices to achieve better overall performance.     

Quantitative assessment of mobile web guidelines conformance

Conformance metrics for the mobile web can play a crucial role as far as engineering mobile websites are concerned, especially if they are automatically obtained. In this way, developers can have an idea in numeric terms of how suitable their developments are for mobile devices. However, there are a plethora of devices with their own particular features (screen size, formats support, etc.) that restrict a unified automatic assessment process. This paper proposes a tool-supported method for device-tailored assessment in terms of conformance with Mobile Web Best Practices 1.0, including the definition of five quantitative metrics for automatically measuring mobile web conformance: Navigability, Page layout, Page definition, User input and Overall score. The behaviour of these metrics was analysed for different devices and different web paradigms, both mobile web pages and their equivalent desktop pages. As expected, the results show that mobile web pages on more capable devices score higher. In addition, 20 users took part in an experiment aimed at discovering how conformance-based scores relate to usability dimensions. The results demonstrate that automatic scoring approaches strongly correlate with usability scores obtained by direct observation, such as task completion time and user satisfaction. This correlation is even stronger for the device-tailored assessment than the one that assumes a general profile for all devices. For instance, results show a strong negative correlation between Overall score and task completion time: ρ (9) = −0.81, (p < 0.05) for the generalist approach and ρ (9) = −0.88 for the device-tailored one, entailing that mobile web guidelines and the metrics based on their conformance capture usability aspects. This result challenges the widely accepted belief that conformance to guidelines does not imply more usable web pages, at least for web accessibility conformance.     

基于隐马尔可夫模型的兴趣迁移模式发现

Web挖掘的一个重要研究方向是发现用户的迁移模式。一般来说,用户的迁移具有某种目的性。这种目的性表现为用户对某种概念的兴趣。文中提出基于隐马尔可夫模型的兴趣迁移模式发现方法,用于发现这种带有某种兴趣的用户迁移模式,这种模式实质上是一种特殊的关联规则。在这种方法中,作者首先根据用户的访问记录定义一个隐马尔可夫模型,然后提出一种新的增量发现算法Increase_R用于发现兴趣迁移模式,同时给出了证明以说明该算法可以发现所有的兴趣迁移模式。     

集成Web使用挖掘和内容挖掘的用户浏览兴趣迁移挖掘算法

提出了一种集成Web使用挖掘和内容挖掘的用户浏览兴趣迁移模式的模型和算法。介绍了Web页面及其聚类。通过替代用户事务中的页面为相应聚类的方法得到用户浏览兴趣序列。从用户浏览兴趣序列中得到用户浏览兴趣迁移模式。该模型对于网络管理者理解用户的行为特征和安排Web站点结构有较大的意义。     

Why structure and genre matter for users of digital information: A longitudinal experiment with readers of a web-based newspaper

In an effort to understand the impact of designing for digital genres on users’ mental representations of structure, a two-phase study was conducted. In phase 1, six expert news readers and a panel of HCI experts were solicited for input regarding genre-conforming and genre-violating web news page design, navigation, and story categorization. In phase 2, a longitudinal experiment with a group of 25 novice web news readers who were exposed to one of the two designs over 5 sessions is reported. During these sessions a variety of user data were captured, including: comprehension (recall, recognition), usability (time on task, accuracy, user satisfaction), and navigation (path length, category node hits).The between-group difference of web site design was significant for comprehension, usability, and navigation with the users of the genre-conforming design demonstrating better performance. The within-group difference of time was significant across these three measures as well, with performance improving over time. No interaction effect was found between web site design and time on comprehension or usability. However, a surprising interaction effect was found on navigation; specifically the breadth of navigation (i.e. the number of nodes visited for two classes of tasks) increased over time more dramatically for the genre-violating group than for the genre-conforming group. By examining the changes in these data over time and between the two designs, evidence for the development of users’ mental representations of structure was captured.     

MODELING WEB NAVIGATION USING GRAMMATICAL INFERENCE

In this article, a method that models user navigation on the web, as opposed to a single website, is presented, aiming to assist the user by recommending pages. User modeling is done through data mining of web usage logs, resulting in aggregate, rather than personal models. The proposed approach extends grammatical inference methods by introducing an extra merging criterion, which examines the semantic similarity of automaton states. The experimental results showed that the method does indeed facilitate the modeling of web navigation, which was not possible with the existing web usage mining methods. However, a content-based recommendation model is shown to still outperform the proposed method, which suggests that the knowledge of the navigation sequence does not contribute to the recommendation process. This is due to the thematic cohesion of navigation sessions, in comparison to the large thematic diversity of web usage data. Among three variants of the proposed method, the one based on Blue Fringe, that examines a larger space of possible merges, performs better.     

Hybrid job offer recommender system in a social network

Recommender systems (RSs) play a very important role in web navigation, ensuring that the users easily find the information they are looking for. Today's social networks contain a large amount of information and it is necessary that they employ a mechanism that will guide users to the information they are interested in. However, to be able to recommend content according to user preferences, it is necessary to analyse their profiles and determine their preferences. The present work proposes a job offer RS for a career‐oriented social network. The recommendation system is a hybrid, it consists of a case‐based reasoning (CBR) system and an argumentation framework, based on a multi‐agent system (MAS) architecture. The CBR system uses a series of metrics and similar cases to decide whether a job offer is likely to be recommended to a user. Besides, the argumentation framework extends the system with an argumentation CBR, through which old and similar cases can be obtained from the CBR system. Finally, a discussion process is established amongst the agents who debate using their experience from past cases to take a final decision.     

Modeling users on the World Wide Web based on cognitive factors,navigation behavior and clustering techniques

This paper focuses on modeling users’ cognitive styles based on a set of Web usage mining techniques on user navigation patterns and clickstream data. Main aim is to investigate whether specific clustering techniques can group users of particular cognitive style using measures obtained from psychometric tests and content navigation behavior. Three navigation metrics are proposed and utilized to find identifiable groups of users that have similar navigation patterns in relation to their cognitive style. The proposed work has been evaluated with two user studies which entail a psychometric-based survey for extracting the users’ cognitive styles, combined with a real usage scenario of users navigating in a controlled Web 2.0 environment. A total of 106 participants of age between 17 and 25 participated in the study providing interesting insights with respect to cognitive styles and navigation behavior of users. Studies like the reported one can be useful for modeling users and assist adaptive Web 2.0 environments to organize and present information and functionalities in an adaptive format to diverse user groups.     

The Effects of Visualization and Synchronization on Clustered-Based Mobile Web Search

ABSTRACT

Despite the increasing use of mobile web in our everyday lives, mobile web search remains a challenging task mainly due to the intensive scrolling inherent in linear presentation of search engine results (SERs) on the small screen of a mobile device. Drawing on the cognitive load theory and information foraging theory, this study aims to improve user performance in mobile web search by proposing two new artifacts—radial visualization of SERs clusters and synchronization of clusters and individual SERs presentations. These artifacts are hypothesized to improve search efficiency and/or navigation efficiency without affecting search effectiveness. This study also examines a possible moderating effect of search task type (open-ended vs. close-ended tasks). We implemented four mobile web search systems that reflect four combinations of different visualization and synchronization settings and empirically evaluated them using a controlled experiment. The results show that the radial visualization improves search efficiency and navigation efficiency, particularly for the open-ended tasks. In addition, synchronous presentation improves navigation efficiency in terms of path similarity.     

Creating recommendations on electronic books: A collaborative learning implicit approach

Recommender systems appear among other reasons with the purpose to improve web information overload and ease information recovery. This kind of systems aid users to find contents in a non-difficult way and with minimal effort. Even though, a great number of these systems performance requires contents to be explicitly rated in order to determine user’s interest. When interacting with electronic books this performance may alter users reading and understanding patterns as they are asked to stop reading and rate the content. Therefore, the analysis of user behavior, preferences and reading background can be considered suitable for a recommender system to build collective web knowledge in a collaborative learning context. This way, recommender system can assist users in finding contents of their interest without explicit rating based on previous constructed knowledge. The goal of this research is to propose an architecture to build a content recommendation platform based on eBook reading user behavior, allowing users to learn about the digital content collaboratively. This platform is formed by web readers’ community that aids members in finding contents of their interest in an automatic way and with minimal effort.     

Improving the prediction of page access by using semantically enhanced clustering

There are many parameters that may affect the navigation behaviour of web users. Prediction of the potential next page that may be visited by the web user is important, since this information can be used for prefetching or personalization of the page for that user. One of the successful methods for the determination of the next web page is to construct behaviour models of the users by clustering. The success of clustering is highly correlated with the similarity measure that is used for calculating the similarity among navigation sequences. This work proposes a new approach for determining the next web page by extending the standard clustering with the content-based semantic similarity method. Semantics of web-pages are represented as sets of concepts, and thus, user session are modelled as sequence of sets. As a result, session similarity is defined as an alignment of two sequences of sets. The success of the proposed method has been shown through applying it on real life web log data.     

Measuring website quality: asymmetric effect of user satisfaction

Website quality measurement tools have been largely static and have struggled to determine relevant attributes of user satisfaction. This study compares and contrasts attributes of user satisfaction based on usability guidelines seeking to identify practical easy-to-administer measurement tools. The website users assessed business school homepages according to six criteria and fulfilled a randomly assigned yet typical task. After completing the task, respondents assessed the same six website quality/satisfaction criteria again. The consumer–product relationship seems similar to the link between a user and a website. User satisfaction, just like consumer satisfaction, is asymmetric and non-linear. Content and navigation have been identified as key ingredients when users judged website quality, alerting web designers and website practitioners to focus more closely on those attributes. Similar lessons can be drawn for marketing professionals, who typically supervise or determine the content, structure and other website facets.     

Navigation techniques for small-screen devices: An evaluation on maps and web pages

Several techniques have been proposed to support user navigation of large information spaces (e.g., maps or web pages) on small-screen devices such as PDAs and Smartphones. In this paper, we present the results of an evaluation that compared three of these techniques to determine how they might affect performance and satisfaction of users. Two of the techniques are quite common on mobile devices: the first one (DoubleScrollbar) is the standard combination of two scrollbars for separate horizontal and vertical scrolling with zoom buttons to change the scale of the information space, the second one (Grab&Drag) enables users to navigate the information space by directly dragging its currently displayed portion, while zooming is handled through a slider control. The last technique (Zoom-Enhanced Navigator or ZEN) is an extension and adaptation to mobile screens of Overview&Detail approaches, which are based on displaying an overview of the information space together with a detail view of a portion of that space. In these approaches, navigation is usually supported by (i) highlighting in the overview which portion of space is displayed in the detail view, and (ii) allowing users to move the highlight within the overview area to change the corresponding portion of space in the detail area. Our experimental evaluation concerned tasks involving maps as well as web page navigation. The paper analyzes in detail the obtained results in terms of task completion times, number and duration of user interface actions, accuracy of the gained spatial knowledge, and subjective preferences.     

Computer display control and interaction using eye‐gaze

Innovative systems for user‐computer interaction based on the user's eye‐gaze behavior have important implications for various applications. Examples include user navigation in large images, typical of astronomy or medicine, and user selection and viewing of multiple video streams. Typically, a web environment is used for these applications. System latency must be negligible, while system obtrusiveness must be small. This paper describes the implementation and initial experimentation on such an innovative system.     

Friendly web services selection exploiting fuzzy formal concept analysis

This work describes a system for supporting the user in the discovery of semantic web services, taking into account personal requirements and preference. Goal is to model an ad-hoc service request by selecting conceptual terms rather than using strict syntax formats. Through a concept-based navigation mechanism indeed, the user discovers conceptual terminology associated to the web resources and uses it to generate an appropriate service request which syntactical matches the names of input/output specifications. The approach exploits the fuzzy formal concept analysis for modeling concepts and relative relationships elicited from web resources. After the request formulation and submission, the system returns the list of semantic web services that match the user query.