Mobile Web Design and Usability

The purpose of this study is to identify the best practices in designing mobile website layouts. It includes research on the current design trends for the mobile web and discusses the future for mobile website interaction. It includes interviews of industry professionals who give their insight on experiences in designing and developing mobile websites. A user experience survey conducted compares a desktop version of a website to its mobile version counterpart, testing users’ preferences for mobile websites in the following areas: navigation, ability to search, and design. The results of this study can be used to improve the mobile web browsing experience through recommendations for mobile web development and design

Context modelling for just-in-time mobile information retrieval (JIT-MobIR)

Mobile users have the capability of accessing information anywhere at any time with the introduction of mobile browsers and mobile web search. However, the current mobile browsers are implemented without considering the characteristics of mobile searches. As a result, mobile users need to devote time and effort in order to retrieve relevant information from the web in mobile devices. On the other hand, mobile users often request information related to their surroundings, which is also known as context. This recognizes the importance of including context in information retrieval. Besides, the availability of the embedded sensors in mobile devices has supported the recognition of context. In this study, the context acquisition and utilization for mobile information retrieval are proposed. The "just-in-time" approach is exploited in which the information that is relevant to a user is retrieved without the user requesting it. This will reduce the mobile user's effort, time and interaction when retrieving information in mobile devices. In this paper, the context dimensions and context model are presented. Simple experiments are shown where user context is predicted using the context model

Mnews: A Study of Multilingual News Search Interfaces

With the global expansion of the Internet and the World Wide Web, users are becoming increasingly diverse, particularly in terms of languages. In fact, the number of polyglot Web users across the globe has increased dramatically. However, even such multilingual users often continue to suffer from unbalanced and fragmented news information, as traditional news access systems seldom allow users to simultaneously search for and/or compare news in different languages, even though prior research results have shown that multilingual users make significant use of each of their languages when searching for information online. Relatively little human-centered research has been conducted to better understand and support multilingual user abilities and preferences. In particular, in the fields of cross-language and multilingual search, the majority of research has focused primarily on improving retrieval and translation accuracy, while paying comparably less attention to multilingual user interaction aspects. The research presented in this thesis provides the first large-scale investigations of multilingual news consumption and querying/search result selection behaviors, as well as a detailed comparative analysis of polyglots’ preferences and behaviors with respect to different multilingual news search interfaces on desktop and mobile platforms. Through a set of 4 phases of user studies, including surveys, interviews, as well as task-based user studies using crowdsourcing and laboratory experiments, this thesis presents the first human-centered studies in multilingual news access, aiming to drive the development of personalized multilingual news access systems to better support each individual user

Cross-display attention switching in mobile interaction with large displays

Mobile devices equipped with features (e.g., camera, network connectivity and media player) are increasingly being used for different tasks such as web browsing, document reading and photography. While the portability of mobile devices makes them desirable for pervasive access to information, their small screen real-estate often imposes restrictions on the amount of information that can be displayed and manipulated on them. On the other hand, large displays have become commonplace in many outdoor as well as indoor environments. While they provide an efficient way of presenting and disseminating information, they provide little support for digital interactivity or physical accessibility. Researchers argue that mobile phones provide an efficient and portable way of interacting with large displays, and the latter can overcome the limitations of the small screens of mobile devices by providing a larger presentation and interaction space. However, distributing user interface (UI) elements across a mobile device and a large display can cause switching of visual attention and that may affect task performance. This thesis specifically explores how the switching of visual attention across a handheld mobile device and a vertical large display can affect a single user's task performance during mobile interaction with large displays. It introduces a taxonomy based on the factors associated with the visual arrangement of Multi Display User Interfaces (MDUIs) that can influence visual attention switching during interaction with MDUIs. It presents an empirical analysis of the effects of different distributions of input and output across mobile and large displays on the user's task performance, subjective workload and preference in the multiple-widget selection task, and in visual search tasks with maps, texts and photos. Experimental results show that the selection of multiple widgets replicated on the mobile device as well as on the large display, versus those shown only on the large display, is faster despite the cost of initial attention switching in the former. On the other hand, a hybrid UI configuration where the visual output is distributed across the mobile and large displays is the worst, or equivalent to the worst, configuration in all the visual search tasks. A mobile device-controlled large display configuration performs best in the map search task and equal to best (i.e., tied with a mobile-only configuration) in text- and photo-search tasks

Understanding search behaviour on mobile devices

Web search on hand-held devices has become enormously common and popular. Although a number of studies have revealed how users interact with search engine result pages (SERPs) on desktop monitors, there are still only few studies related to user interaction in mobile web search, and search results are shown in a similar way whether on a mobile phone or a desktop. Therefore, it is still difficult to know what happens between users and SERPs while searching on small screens, and this means that the current presentation of SERPs on mobile devices may not be the best. According to the findings from previous studies, including our earlier work, we can confirm that search behaviour on touch-enabled mobile devices is different from behaviour with desktop screens, and so we need to consider a different SERP presentation design for mobile devices. In this thesis, we explore several user interactions during search with the aim of improving search experience on smartphones. First, one remarkable trend of mobile devices is their enlargement of screen sizes during the last few years. This leads us to look for differences in search behaviour on different sized small screens, and if there are any, to suggest better presentation of search results for each screen size. In the first study, we investigated search performance, behaviour, and user satisfaction on three small screens (3.6 inches for early smartphones, 4.7 inches for recent smart-phones and 5.5 inches for phablets). We found no significant differences with respect to the efficiency of carrying out tasks. However, participants exhibited different search behaviours on the small, medium, and large sizes of small screens, respectively: a higher chance of scrolling with the worst user satisfaction on the smallest screen; fast information extraction with some hesitation before selecting a link on the medium screen; and less eye movements on top links on the largest screen. These results suggest that the presentation of web search results for each screen size needs to take into account differences in search behaviour. Second, although people are familiar with turning pages horizontally while reading books, vertical scrolling is the standard option that people have available while searching on mobile devices. So following a suggestion from the first study, in the second study we explored the effect of horizontal and vertical viewport control types (pagination versus scrolling) with various positions of a correct answer in mobile web search. Our findings suggest that although users are more familiar with scrolling, participants spent less time to find the correct answer with pagination, especially when the relevant result is located beyond the page fold. In addition, participants using scrolling exhibited less interest in lower-ranked results even if the documents were relevant. The overall result indicates that it is worthwhile providing different viewport controls for better search experiences in mobile web search. Third, snippets occupy the biggest space in each search result. Results from a previous study suggested that snippet length affects search performance on a desktop monitor. Due to the smaller screen, the effect seems to be much larger on smartphones. As one possible idea for a SERP presentation design from the first study, we investigated appropriate snippet lengths on mobile devices in the third study. We compared search behaviour with three different snippet lengths, that is, one line, two to three lines, and six or more lines of snippets on mobile SERPs. We found that with long snippets, participants needed longer search time for a particular task type, and the longer time consumption provided no better search accuracy. Our findings suggest that this search performance is related to viewport movements and user attention. We expect that our proposed approaches provide ways to understand mobile web search behaviour, and that the findings can be applied to a wide range of research areas such as human-computer integration, information retrieval, and even social science for a better presentation design of SERP on mobile devices

Using Machine Learning to Optimize Web Interactions on Heterogeneous Mobile Systems

The web has become a ubiquitous application development platform for mobile systems. Yet, web access on mobile devices remains an energy-hungry activity. Prior work in the field mainly focuses on the initial page loading stage, but fails to exploit the opportunities for energy-efficiency optimization while the user is interacting with a loaded page. This paper presents a novel approach for performing energy optimization for interactive mobile web browsing. At the heart of our approach is a set of machine learning models, which estimate at runtime the frames per second for a given user interaction input by running the computation-intensive web render engine on a specific processor core under a given clock speed. We use the learned predictive models as a utility function to quickly search for the optimal processor setting to carefully trade responsive time for reduced energy consumption. We integrate our techniques to the open-source Chromium browser and apply it to two representative mobile user events: scrolling and pinching (i.e., zoom in and out). We evaluate the developed system on the landing pages of the top-100 hottest websites and two big.LITTLE heterogeneous mobile platforms. Our extensive experiments show that the proposed approach reduces the system-wide energy consumption by over 36% on average and up to 70%. This translates to an over 17% improvement on energy-efficiency over a state-of-the-art event-based web browser scheduler, but with significantly fewer violations on the quality of service

Modeling Internet as a User-Adapted Speech Service

Proceedings of: 7th International Conference, HAIS 2012, Salamanca, Spain, March 28-30th, 2012.The web has become the largest repository of multimedia information and its convergence with telecommunications is now bringing the benefits of web technology and hybrid artificial intelligence systems to hand-held devices. However, maximizing accessibility is not always the main objective in the design of web applications, specially if it is concerned with facilitating access for disabled people. This way, natural spoken conversation and multimodal conversational agents have been proposed as a solution to facilitate a more natural interaction with these kind of devices. In this paper, we describe a proposal to provide spoken access to Internet information that is valid not only to generate basic applications (e.g., web search engines), but also to develop dialog-based speech interfaces that facilitate a user-adapted access that enhances web services. We describe our proposal and detail several applications developed to provide evidences about the benefits of introducing speech to make the enormous web content accessible to all mobile phone users.Research funded by projects CICYT TIN2011-28620- C02-01, CICYT TEC2011-28626-C02-02,CAM CONTEXTS (S2009/TIC-1485), and DPS2008-07029-C02-02.Publicad

Understanding Mobile Search Task Relevance and User Behaviour in Context

Improvements in mobile technologies have led to a dramatic change in how and when people access and use information, and is having a profound impact on how users address their daily information needs. Smart phones are rapidly becoming our main method of accessing information and are frequently used to perform `on-the-go' search tasks. As research into information retrieval continues to evolve, evaluating search behaviour in context is relatively new. Previous research has studied the effects of context through either self-reported diary studies or quantitative log analysis; however, neither approach is able to accurately capture context of use at the time of searching. In this study, we aim to gain a better understanding of task relevance and search behaviour via a task-based user study (n=31) employing a bespoke Android app. The app allowed us to accurately capture the user's context when completing tasks at different times of the day over the period of a week. Through analysis of the collected data, we gain a better understanding of how using smart phones on the go impacts search behaviour, search performance and task relevance and whether or not the actual context is an important factor.Comment: To appear in CHIIR 2019 in Glasgow, U