Taking control of web browsing

Adherence to accessibility guidelines for Web pages does not necessarily guarantee a usable or satisfying Web experience for all persons with disabilities. The needs of many of these individuals fall outside the guidelines for accessible content that most Web authors take into consideration. Many of these users wish, for example, that they simply could ‘enlarge’ what is on a Web page. They also express the wish that pages would be ‘less confusing’. To meet these needs, Web browsers and various software applications provide for a variety of ways in which page presentations can be altered. The effects of these alterations often have unexpected consequences. Some designs accommodate these alterations better than others. This article discusses one such application that allows users to control features of Web page presentation and explores design features that facilitate such control.     

Tactile web browsing for blind people

Information on the World Wide Web becomes more and more important for our society. For blind people this is a chance to access more information for their everyday life. In this paper we propose novel methods to present web pages including graphical information on a tactile output device. We present a Mozilla Firefox Extension for the tactile rendering of web pages and for the handling of user interactions. This approach benefits from the Firefox built-in web page handling including parsing of HTML documents, formatting with cascading style sheets (CSS), handling of dynamic web content controlled by JavaScript code, etc. Graphical information can be explored and filtered interactively in a special mode for raster images and Scalable Vector Graphics (SVG). Mathematical expressions encoded in the mathematical markup language (MathML) are transformed directly into LaTeX or into a notation for blind people. The tactile web browser supports feedback that is provided via voice output.

B-hist: Entity-centric search over personal web browsing history

Web Search is increasingly entity centric; as a large fraction of common queries target specific entities, search results get progressively augmented with semi-structured and multimedia information about those entities. However, search over personal web browsing history still revolves around keyword-search mostly. In this paper, we present a novel approach to answer queries over web browsing logs that takes into account entities appearing in the web pages, user activities, as well as temporal information. Our system, B-hist, aims at providing web users with an effective tool for searching and accessing information they previously looked up on the web by supporting multiple ways of filtering results using clustering and entity-centric search. In the following, we present our system and motivate our User Interface (UI) design choices by detailing the results of a survey on web browsing and history search. In addition, we present an empirical evaluation of our entity-based approach used to cluster web pages.     

Loosely-coupled approach towards multi-modal browsing

Contemplating the concept of universal-access multi-modal browsing comes as one of the emerging killer technologies that promises broader and more flexible access to information, faster task completion, and advanced user experience. Inheriting the best from GUI and speech, based on the circumstances, hardware capabilities, and environment, multi-modalitys great advantage is to provide application developers with a scalable blend of input and output channels that may accommodate any user, device, and platform. This article describes a flexible multi-modal browser architecture, named Ferda the Ant, which reuses uni-modal browser technologies available for VoiceXML, WML, and HTML browsing. A central component, the Virtual Proxy, acts as a synchronization coordinator. This browser architecture can be implemented in either a single client configuration, or by distributing the browser components across the network. We have defined and implemented a synchronization protocol to communicate the changes occurring in the context of a component browser to the other browsers participating in the multi-modal browser framework. Browser wrappers implement the required synchronization protocol functionality at each of the component browsers. The component browsers comply with existing content authoring standards, and we have designed a set of markup-level authoring conventions that facilitate maintaining the browser synchronization .     

Input devices for web browsing: age and hand effects

The work reported in this paper examined performance on a mixed pointing and data entry task using direct and indirect positioning devices for younger, middle-aged, and older adults (n=72) who were experienced mouse users. Participants used both preferred and non-preferred hands to perform an item selection and text entry task simulating a typical web page interaction. Older adults performed more slowly than middle-aged adults who in turn performed more slowly than young adults. Performance efficiency was superior with the mouse for older adults only on the first two trial blocks. Thereafter mouse and light pen yielded equivalent performance. For other age groups, mouse and light pen were equivalent at all points of practice. Contrary to prior research revealing superior performance with a light pen for pure pointing tasks, these results suggest that older adults may initially perform worse with a light pen than a mouse for mixed tasks.     

Mining linguistic browsing patterns in the world wide web

 World-wide-web applications have grown very rapidly and have made a significant impact on computer systems. Among them, web browsing for useful information may be most commonly seen. Due to its tremendous amounts of use, efficient and effective web retrieval has thus become a very important research topic in this field. Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for a certain purpose. In this paper, we use the data mining techniques to discover relevant browsing behavior from log data in web servers, thus being able to help make rules for retrieval of web pages. The browsing time of a customer on each web page is used to analyze the retrieval behavior. Since the data collected are numeric, fuzzy concepts are used to process them and to form linguistic terms. A sophisticated web-mining algorithm is thus proposed to find relevant browsing behavior from the linguistic data. Each page uses only the linguistic term with the maximum cardinality in later mining processes, thus making the number of fuzzy regions to be processed the same as the number of the pages. Computational time can thus be greatly reduced. The patterns mined out thus exhibit the browsing behavior and can be used to provide some appropriate suggestions to web-server managers.     

Adapting web pages using graph partitioning algorithms for user-centric multi-device web browsing

In the era of ubiquitous computing, applications are emerging to benefit from using devices of different users and different capabilities together. This paper focuses on user-centric web browsing using multiple devices, where content of a web page is partitioned, adapted and allocated to devices in the vicinity. We contribute two novel web page partitioning algorithms. They differ from existing approaches by allowing for both, automatic and semi-automatic partitioning. On the one hand, this provides good automatic, web page independent results by utilizing sophisticated structural pre- and postprocessing of the web page. On the other hand, these results can be improved by considering additional semantic information provided through user-generated web page annotations. We further present a performance evaluation of our algorithms. Moreover, we contribute the results of a user study. These clearly show that (1) our algorithms provide good automatic results and (2) the application of user-centric, annotation-based semantic information leads to a significantly higher user satisfaction.     

Using RSS feeds for effective mobile web browsing

While mobile phones are becoming more popular, wireless communication vendors and device manufacturers are seeking new applications for their products. Access to the large corpus of Internet information is a very prominent field. However, the technical limitations of mobile devices pose many challenges. Browsing the Internet using a mobile phone is a large scientific and cultural challenge. Web content must be adapted before it can be accessed by a mobile browser. This work presents a new methodology that uses Really Simple Syndication (RSS) feeds for the adaptation of web content for use in mobile phones. This methodology is based on concrete design guidelines and supports different viewing modes. The mobile tool provided using the RSS feeds is evaluated based on user-centered evaluation and the results are presented.     

Nonstationary Poisson modeling of web browsing session arrivals

In this paper we show that daily web session arrivals are nonstationary Poissonian with a rate surprisingly stable, i.e., changing only once per 24 hours in all the examined cases.     

Exploiting semantic annotation to supporting user browsing on the web

The aim of this paper is to support user browsing on semantically heterogeneous information spaces. In advance of a user’s explicit actions, his search context should be predicted by the locally annotated resources in his access histories. We thus exploit semantic transcoding method and measure the relevance between the estimated model of user intention and the candidate resources in web spaces. For these experiments, we simulated the scenario of comparison-shopping systems on the testing bed organized by twelve online stores in which images are annotated with semantically heterogeneous metadata.     

On web user tracking of browsing patterns for personalised advertising

On today’s Web, users trade access to their private data for content and services. App and service providers want to know everything they can about their users, in order to improve their product experience. Also, advertising sustains the business model of many websites and applications. Efficient and successful advertising relies on predicting users’ actions and tastes to suggest a range of products to buy. Both service providers and advertisers try to track users’ behaviour across their product network. For application providers this means tracking users’ actions within their platform. For third-party services following users, means being able to track them across different websites and applications. It is well known how, while surfing the Web, users leave traces regarding their identity in the form of activity patterns and unstructured data. These data constitute what is called the user’s online footprint. We analyse how advertising networks build and collect users footprints and how the suggested advertising reacts to changes in the user behaviour.     

Manipulating perceived social presence through the web interface and its impact on attitude towards online shopping

Electronic commerce typically lacks human warmth and sociability, since it is more impersonal, anonymous and automated than traditional face-to-face commerce. This paper explores how human warmth and sociability can be integrated through the web interface to positively impact consumer attitudes towards online shopping. An empirical study was undertaken to investigate the impact of various levels of socially rich text and picture design elements on the perception of online social presence and its subsequent effect on antecedents of attitudes towards websites. Higher levels of perceived social presence are shown to positively impact the perceived usefulness, trust and enjoyment of shopping websites, leading to more favourable consumer attitudes. Implications of these finding for practitioners and future research are outlined.     

A web browsing system for cellular-phone users based on adaptive presentation

Cellular phones are widely used to access the Web. However, most available Web pages are designed for desktop PCs, and it is inconvenient to browse these large Web pages on a cellular phone with a small screen and poor interfaces. Users who browse a Web page on a cellular phone have to scroll through the whole page to find the desired content, and must then search and scroll within that content in detail to get useful information. This paper describes the design and implementation of a novel Web browsing system for cellular phones. This system includes a Web page overview to reduce scrolling operations when finding objective content within the page. Furthermore, it adaptively presents content according to its characteristics to reduce burdensome operations when searching within content.     

Extracting user web browsing patterns from non-content network traces: The online advertising case study

Online advertising is a rapidly growing industry currently dominated by the search engine ’giant’ Google. In an attempt to tap into this huge market, Internet Service Providers (ISPs) started deploying deep packet inspection techniques to track and collect user browsing behavior. However, these providers have the fear that such techniques violate wiretap laws that explicitly prevent intercepting the contents of communication without gaining consent from consumers. In this paper, we explore how it is possible for ISPs to extract user browsing patterns without inspecting contents of communication.Our contributions are threefold. First, we develop a methodology and implement a system that is capable of extracting web browsing features from stored non-content based network traces, which could be legally shared. When such browsing features are correlated with information collected by independently crawling the Web, it becomes possible to recover the actual web pages accessed by clients. Second, we evaluate our system on the Internet and check that it can successfully recover user browsing patterns with high accuracy.     

Multimodal sensing, recognizing and browsing group social dynamics

Group social dynamics is crucial for determining whether a meeting was well organized and the conclusion well reasoned. In this paper, we propose multimodal approaches for sensing, recognition and browsing of social dynamics, specifically human semantic interactions and group interests in small group meetings. Unlike physical interactions (e.g., turn-taking and addressing), the human interactions considered here are incorporated with semantics, i.e., user intention or attitude toward a topic. Group interests are defined as episodes in which participants engaged in an emphatic and heated discussion. We adopt multiple sensors, such as video cameras, microphones and motion sensors for meeting capture. Multimodal methods are proposed for human interaction recognition and group interest recognition based on a variety of features. A graphical user interface, the MMBrowser, is presented for browsing group social dynamics. Experimental results have demonstrated the feasibility of the proposed approaches.     

Supporting serendipity: Using ambient intelligence to augment user exploration for data mining and web browsing

Serendipity is the making of fortunate discoveries by accident, and is one of the cornerstones of scientific progress. In today's world of digital data and media, there is now a vast quantity of material that we could potentially encounter, and so there is an increased opportunity of being able to discover interesting things. However, the availability of material does not imply that we will be able to actually find it; the sheer quantity of data mitigates against us being able to discover the interesting nuggets.This paper explores approaches we have taken to support users in their search for interesting and relevant information. The primary concept is the principle that it is more useful to augment user skills in information foraging than it is to try and replace them. We have taken a variety of artificial intelligence, statistical, and visualisation techniques, and combined them with careful design approaches to provide supportive systems that monitor user actions, garner additional information from their surrounding environment and use this enhanced understanding to offer supplemental information that aids the user in their interaction with the system.We present two different systems that have been designed and developed according to these principles. The first system is a data mining system that allows interactive exploration of the data, allowing the user to pose different questions and understand information at different levels of detail. The second supports information foraging of a different sort, aiming to augment users browsing habits in order to help them surf the internet more effectively. Both use ambient intelligence techniques to provide a richer context for the interaction and to help guide it in more effective ways: both have the user as the focal point of the interaction, in control of an iterative exploratory process, working in indirect collaboration with the artificial intelligence components.Each of these systems contains some important concepts of their own: the data mining system has a symbolic genetic algorithm which can be tuned in novel ways to aid knowledge discovery, and which reports results in a user-comprehensible format. The visualisation system supports high-dimensional data, dynamically organised in a three-dimensional space and grouped by similarity. The notions of similarity are further discussed in the internet browsing system, in which an approach to measuring similarity between web pages and a user's interests is presented. We present details of both systems and evaluate their effectiveness.     

Boosting web video categorization with contextual information from social web

Web video categorization is a fundamental task for web video search. In this paper, we explore web video categorization from a new perspective, by integrating the model-based and data-driven approaches to boost the performance. The boosting comes from two aspects: one is the performance improvement for text classifiers through query expansion from related videos and user videos. The model-based classifiers are built based on the text features extracted from title and tags. Related videos and user videos act as external resources for compensating the shortcoming of the limited and noisy text features. Query expansion is adopted to reinforce the classification performance of text features through related videos and user videos. The other improvement is derived from the integration of model-based classification and data-driven majority voting from related videos and user videos. From the data-driven viewpoint, related videos and user videos are treated as sources for majority voting from the perspective of video relevance and user interest, respectively. Semantic meaning from text, video relevance from related videos, and user interest induced from user videos, are combined to robustly determine the video category. Their combination from semantics, relevance and interest further improves the performance of web video categorization. Experiments on YouTube videos demonstrate the significant improvement of the proposed approach compared to the traditional text based classifiers.     

The interaction effects of familiarity, breadth and media usage on web browsing experience

Web technology is changing rapidly every day and the internet has become a lifestyle for people all over the world. The power of the web has changed the way people communicate and do business. With the advance of the internet era, a successful website becomes a critical factor for the success of most businesses. Website design is not only about the look of the website. There are many other factors to consider. A well-designed site can induce users to engage in the website, help them find what they are looking for, and understand where exactly they are on the website. This study investigates the user’s perception disorientation, engagement, and intent to use a website in the future by manipulating these three basic factors into eight different experimental conditions. With 2 × 2 × 2 experimental design with content familiarity, site breadth, and media richness in website systems, this study suggests that both the main effects and the interaction effects of the experiment factors are significant. This implies that one or more factors can compensate for the weakness of other factors. Furthermore different people have preferences for different factors; therefore website design should not solely focus on a single factor, but should address all of these factors in accordance with the objective of the business.