Social NUI: Social perspectives in natural user interfaces

Natural User Interfaces (NUI) offer rich ways for interacting with the digital world that make innovative use of existing human capabilities. They include and often combine different input modalities such as voice, gesture, eye gaze, body interactions, touch and touchless interactions. However much of the focus of NUI research and development has been on enhancing the experience of individuals interacting with technology. Effective NUIs must also acknowledge our innately social characteristics, and support how we communicate with each other, play together, learn together and collaboratively work together. This workshop concerns the social aspects of NUI. The workshop seeks to better understand the social uses and applications of these new NUI technologies -- how we design these technologies for new social practices and how we understand the use of these technologies in key social contexts.

Modelling user profiles for recommender systems

Recommender systems assist users in finding what they want. The challenging issue is how to efficiently acquire user preferences or user information needs for building personalized recommender systems. This research explores the acquisition of user preferences using data taxonomy information to enhance personalized recommendations for alleviating cold-start problem. A concept hierarchy model is proposed, which provides a two-dimensional hierarchy for acquiring user preferences. The language model is also extended for the proposed hierarchy in order to generate an effective recommender algorithm. Both Amazon.com book and music datasets are used to evaluate the proposed approach, and the experimental results show that the proposed approach is promising.

User centred design for engineering e-government web usability

E-government provides a platform for governments to implement web enabled services that facilitate communication between citizens and the government. However, technology driven design approach and limited understanding of citizens' requirements, have led to a number of critical usability problems on the government websites. Hitherto, there has been no systematic attempt to analyse the way in which theory of User Centred Design (UCD) can contribute to address the usability issues of government websites. This research seeks to fill this gap by synthesising perspectives drawn from the study of User Centred Design and examining them based on the empirical data derived from case study of the Scottish Executive website. The research employs a qualitative approach in the collection and analysis of data. The triangulated analysis of the findings reveals that e-government web designers take commercial development approach and focus only on technical implementations which lead to websites that do not meet citizens' expectations. The research identifies that e-government practitioners can overcome web usability issues by transferring the theory of UCD to practice.

Making usability affordable in the design of e-government services: User-centred design for public sector websites

E-government provides a platform for governments to implement web-enabled services that facilitate communication between citizens and the government. However, technology-driven design approach and limited understanding of citizens' requirements have led to a number of critical usability problems on the government websites. Hitherto, there has been no systematic attempt to analyse the way in which theory of User-Centred Design (UCD) can contribute to address the usability issues of government websites. This research seeks to fill this gap by synthesising perspectives drawn from the study of UCD and examining them based on the empirical data derived from case study of the Scottish Executive (SE) website. The research employs a qualitative approach in the collection and analysis of data. The triangulated analysis of the findings reveals that e-government web designers take commercial development approach and focus only on technical implementations, which lead to websites that do not meet citizens' expectations. The research identifies that e-government practitioners can overcome web usability issues by transferring the theory of UCD to practice. © Copyright 2010 Inderscience Enterprises Ltd.

Three-User Cognitive Channels with Cumulative Message Sharing: An Achievable Rate Region

In this paper, an achievable rate region for the three-user discrete memoryless interference channel with asymmetric transmitter cooperation is derived. The three-user channel facilitates different ways of message sharing between the transmitters. We introduce a manner of noncausal (genie aided) unidirectional message-sharing, which we term cumulative message sharing. We consider receivers with predetermined decoding capabilities, and define a cognitive interference channel. We then derive an achievable rate region for this channel by employing a coding scheme which is a combination of superposition and Gel'fand-Pinsker coding techniques.

Augmenting process elicitation with visual priming: An empirical exploration of user behaviour and modelling outcomes

Business process models have become an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach to process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions similarly to how they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. An empirical investigation comparing both the modelling outputs and participant behaviour of this virtual world role-play elicitor with an S-BPM process modelling tool found that while the modelling approaches of the two groups varied greatly, the virtual world elicitor may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

Cultures of sharing in 3D printing: What can we learn from the licence choices of Thingiverse users?

This article contributes to the discussion by analysing how users of the leading online 3D printing design repository Thingiverse manage their intellectual property (IP). 3D printing represents a fruitful case study for exploring the relationship between IP norms and practitioner culture. Although additive manufacturing technology has existed for decades, 3D printing is on the cusp of a breakout into the technological mainstream – hardware prices are falling; designs are circulating widely; consumer-friendly platforms are multiplying; and technological literacy is rising. Analysing metadata from more than 68,000 Thingiverse design files collected from the site, we examine the licensing choices made by users and explore the way this shapes the sharing practices of the site’s users. We also consider how these choices and practices connect with wider attitudes towards sharing and intellectual property in 3D printing communities. A particular focus of the article is how Thingiverse structures its regulatory framework to avoid IP liability, and the extent to which this may have a bearing on users’ conduct. The paper has three sections. First, we will offer a description of Thingiverse and how it operates in the 3D printing ecosystem, noting the legal issues that have arisen regarding Thingiverse’s Terms of Use and its allocation of intellectual property rights. Different types of Thingiverse licences will be detailed and explained. Second, the empirical metadata we have collected from Thingiverse will be presented, including the methods used to obtain this information. Third, we will present findings from this data on licence choice and the public availability of user designs. Fourth, we will look at the implications of these findings and our conclusions regarding the particular kind of sharing ethic that is present in Thingiverse; we also consider the “closed” aspects of this community and what this means for current debates about “open” innovation.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Designing for user engagement: The ALTC exchange for higher education

The Australasian Society for Computers in Learning in Tertiary Education (ascilite) has recently completed research to inform development of the ALTC Exchange, a new online service for learning and teaching in Australia. The research investigated resource identification and contribution, engagement with the repository and user community, and associated peer review and commentary processes. This article focuses on the data obtained and recommendations developed for engagement of potential end users. It reports a literature review and findings, including an international perspective on the ALTC Exchange, with specific focus on prospective user needs, contexts of use and policies necessary to facilitate engagement of the higher education sector with the ALTC Exchange

Towards a typology of hashtag publics: A large-scale comparative study of user engagement across trending topics

Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Discovering user preferences by using time entries in click-through data to improve search engine results

The search engine log files have been used to gather direct user feedback on the relevancy of the documents presented in the results page. Typically the relative position of the clicks gathered from the log files is used a proxy for the direct user feedback. In this paper we identify reasons for the incompleteness of the relative position of clicks for deciphering the user preferences. Hence, we propose the use of time spent by the user in reading through the document as indicative of user preference for a document with respect to a query. Also, we identify the issues involved in using the time measure and propose means to address them.

End-User Attitudes Towards EDM Use in Construction Project Work: Case Study

This article reports on a cross-sectional case study of a large construction project in which Electronic document management (EDM) was used. Attitudes towards EDM from the perspective of individual end users were investigated. Responses from a survey were combined with data from system usage log files to obtain an overview of attitudes prevalent in different user segments of the total population of 334 users. The survey was followed by semi-structured interviews with representative users. A strong majority of users from all segments of the project group considered EDM as a valuable aid in their work processes, despite certain functional limitations of the system used and the complexity of the information mass. Based on the study a model describing the key factors affecting end user EDM adoption is proposed. The model draws on insight from earlier studies of EDM enabled projects and theoretical frameworks on technology acceptance and success of information systems, as well as the insights gained from the case study.

An analytical model for capacity evaluation of VoIP on HCCA and TCP file transfers over EDCA in an IEEE 802.11e WLAN

In the context of the IEEE 802.11e standard for WLANs, we provide an analytical model for obtaining the maximum number of VoIP calls that can be supported on HCCA, such that the delay QoS constraint of the accepted calls is met, when TCP downloads are coexistent on EDCA. In this scenario, we derive the TCP download throughput by using an analytical model for the case where only TCP sessions are present in the WLAN. We show that the analytical model for combined voice and TCP transfers provides accurate results in comparison with simulations (using ns-2).

An analytical model for the capacity estimation of combined VoIP and TCP file transfers over EDCA in an IEEE 802.11e WLAN

In this paper we develop and numerically explore the modeling heuristic of using saturation attempt probabilities as state dependent attempt probabilities in an IEEE 802.11e infrastructure network carrying packet telephone calls and TCP controlled file downloads, using Enhanced Distributed Channel Access (EDCA). We build upon the fixed point analysis and performance insights in [1]. When there are a certain number of nodes of each class contending for the channel (i.e., have nonempty queues), then their attempt probabilities are taken to be those obtained from saturation analysis for that number of nodes. Then we model the system queue dynamics at the network nodes. With the proposed heuristic, the system evolution at channel slot boundaries becomes a Markov renewal process, and regenerative analysis yields the desired performance measures.The results obtained from this approach match well with ns2 simulations. We find that, with the default IEEE 802.11e EDCA parameters for AC 1 and AC 3, the voice call capacity decreases if even one file download is initiated by some station. Subsequently, reducing the voice calls increases the file download capacity almost linearly (by 1/3 Mbps per voice call for the 11 Mbps PHY).