Graphical history list on world wide web visualisation: A usability paradigm

The World Wide Web (WWW) is a fast emerging technology which enables users to view the information via a web browser such as Internet Explorer and Netscape Navigator.Studies have revealed that users often get ‘lost’ as they navigate deeper and deeper.Information visualisation is adopted by many researchers to construct the graphical representation of history list as text-based imposes a burden on users. Although information visualisation is a useful tool, questions arise on its usability and human short term memory.A prototype of a graphical history list is developed while taking the usability and human short term memory into considerations.The research results have significantly indicated a positive and promising outcome on a usable graphical history list on WWW visualisation

An empirical study of web interface design on small display devices

This paper reports an empirical study that explores the problem of finding a highly-efficient, user-friendly interface design method on small display devices. We compared three models using our PDA interface simulator: presentation optimization method, semantic conversion method, and zooming method. A controlled experiment has been carried out to identify the pros and cons of each method. The results show that of the three interface methods, the zooming method is slightly better than the semantic conversion method, while they both outperform the optimizing presentation method. © 2004 IEEE

Getting Real: A Naturalistic Methodology for Using Smartphones to Collect Mediated Communications

This paper contributes an intentionally naturalistic methodology using smartphone logging technology to study communications in the wild. Smartphone logging can provide tremendous access to communications data from real environments. However, researchers must consider how it is employed to preserve naturalistic behaviors. Nine considerations are presented to this end. We also provide a description of a naturalistic logging approach that has been applied successfully to collecting mediated communications from iPhones. The methodology was designed to intentionally decrease reactivity and resulted in data that were more accurate than self-reports. Example analyses are also provided to show how data collected can be analyzed to establish empirical patterns and identify user differences. Smartphone logging technologies offer flexible capabilities to enhance access to real communications data, but methodologies employing these techniques must be designed appropriately to avoid provoking naturally occurring behaviors. Functionally, this methodology can be applied to establish empirical patterns and test specific hypotheses within the field of HCI research. Topically, this methodology can be applied to domains interested in understanding mediated communications such as mobile content and systems design, teamwork, and social networks

Cost and Benefit of Information Search using Two Different Strategies

Searching for information is one major Internet activities during which information seekers may gain benefit as well as incurred some cost. In general, information seekers seldom employ any search strategy for general browsing to explore information space. On the other hand, in certain situation, they may employ certain search strategy, especially those who engage in a fact-finding activity. The objective of this research is to shed light on how search strategy can be used to gain the maximum benefit of information search activities. It borrows the two-factor theory to group Web design elements into benefit and cost manifested as motivating and hygiene factors. This research employed a laboratory experiment with 235 respondents who were participated on this research voluntarily. Respondents were divided into two groups, namely ‘plan-group’ and ‘unplan-group’. Both groups were given certain tasks related to information search. The experiment was followed by a post experiment survey. The result shows that respondents who were in the ‘plan-group’ perceived less benefit and incurred more cost compared to those in the ‘unplan-group’. The future research is proposed at the end of this manuscript

Web information search and sharing :

制度:新 ; 報告番号:甲2735号 ; 学位の種類:博士(人間科学) ; 授与年月日:2009/3/15 ; 早大学位記番号:新493

Searching or surfing : how do students who use the Web locate information resources?

SIGLEAvailable from British Library Document Supply Centre- DSC:DXN062800 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Identification of re-finding tasks and search difficulty

We address the problem of identifying if users are attempting to re-find information and estimating the level of difficulty of the re-finding task. Identifying re-finding tasks and detecting search difficulties will enable search engines to respond dynamically to the search task being undertaken. To this aim, we conduct user studies and query log analysis to make a better understanding of re-finding tasks and search difficulties. Computing features particularly gathered in our user studies, we generate training sets from query log data, which is used for constructing automatic identification (prediction) models. Using machine learning techniques, our built re-finding identification model, which is the first model at the task level, could significantly outperform the existing query-based identifications. While past research assumes that previous search history of the user is available to the prediction model, we examine if re-finding detection is possible without access to this information. Our evaluation indicates that such detection is possible, but more challenging. We further describe the first predictive model in detecting re-finding difficulty, showing it to be significantly better than existing approaches for detecting general search difficulty. We also analyze important features for both identifications of re-finding and difficulties. Next, we investigate detailed identification of re-finding tasks and difficulties in terms of the type of the vertical document to be re-found. The accuracy of constructed predictive models indicates that re-finding tasks are indeed distinguishable across verticals and in comparison to general search tasks. This illustrates the requirement of adapting existing general search techniques for the re-finding context in terms of presenting vertical-specific results. Despite the overall reduction of accuracy in predictions independent of the original search of the user, it appears that identifying “image re-finding” is less dependent on such past information. Investigating the real-time prediction effectiveness of the models show that predicting ``image'' document re-finding obtains the highest accuracy early in the search. Early predictions would benefit search engines with adaptation of search results during re-finding activities. Furthermore, we study the difficulties in re-finding across verticals given some of the established indications of difficulties in the general web search context. In terms of user effort, re-finding “image” vertical appears to take more effort in terms of number of queries and clicks than other investigated verticals, while re-finding “reference” documents seems to be more time consuming when there is a longer time gap between the re-finding and corresponding original search. Exploring other features suggests that there could be particular difficulty indications for the re-finding context and specific to each vertical. To sum up, this research investigates the issue of effectively supporting users with re-finding search tasks. To this end, we have identified features that allow for more accurate distinction between re-finding and general tasks. This will enable search engines to better adapt search results for the re-finding context and improve the search experience of the users. Moreover, features indicative of similar/different and easy/difficult re-finding tasks can be employed for building balanced test environments, which could address one of the main gaps in the re-finding context