Computing and Information Systems - Research Publications
Permanent URI for this collection
Search Results
1 - 7 of 7
-
ItemThe Future of Emotion in Human-Computer Interaction(ACM, 2022)Emotion has been studied in HCI for two decades, with specific traditions interested in sensing, expressing, transmitting, modelling, experiencing, visualizing, understanding, constructing, regulating, manipulating or adapting to emotion in human-human and human-computer interactions. This CHI 2022 workshop on the Future of Emotion in Human-Computer Interaction brings together interested researchers to take stock of research on emotion in HCI to-date and to explore possible futures. Through group discussion and collaborative speculation we will address questions such as: What are the relationships between digital technology and human emotion? What roles does emotion play in HCI research? How should HCI researchers conceptualize emotion? When should HCI researchers use interdisciplinary theories of emotion or create new theory? Can specific emotions be designed for, and where is this knowledge likely to be applied? What are the implications of emotion research for design, ethics and wellbeing? What is the future of emotion in human-computer interaction?
-
ItemNo Preview AvailableUser Models, Metrics and Measures of Search: A Tutorial on the C/W/L Evaluation Framework(ACM, 2021-03-14)Evaluation is central to Information Retrieval, and is how we compare the quality of systems. One important principle of evaluation is that the measured score should reflect the user's experience with the system. Hence, there should be direct connection between how users interact with the system and the characteristics of the metric. In this tutorial we introduce the C/W/L approach to user modeling and show how different user models lead to different metrics. We then describe the recent innovations and approaches to evaluation that it has facilitated. The tutorial is presented as a mix of on-line synchronous lecture, pre-recorded in-depth videos, and hands-on activities using theC/W/L toolkit for participants' own evaluation tasks. A followup consultation session is also provided, to allow extended questions and individual discussion with the four presenters.
-
ItemThe PhD Journey: Reaching Out and Lending a Hand(Association for Computing Machinery (ACM), 2021)Undertaking a PhD is a challenging yet fulfilling experience. PhD candidates become deeply involved in developing a myriad of skills over many vital facets, including (but not limited to): (i) the development of their research ideas; (ii) learning how to conduct their research; (iii) engaging with others about their research — both locally and internationally; (iv) developing a profile as an independent researcher; and (v) developing their teaching portfolio. Of course, a candidate is likely to encounter many highs and lows during their candidature. Periods of turbulence can be overcome through the application of various techniques to adapt and learn from these experiences. This tutorial will partly aim to introduce attendees to several techniques to help them advance in the PhD process. It will be presented by two recent PhD graduates in the field of Interactive Information Retrieval (IIR), who are both close enough to their respective times as PhD students to remember the highs and lows of PhD life, yet be far enough removed from the process that they can adequately reflect and provide insights into their own experiences — both good and bad. This tutorial will empower attendees to share their own do’s and don’ts, review their practices for success, and refine what productivity strategies work for them. It will provide an impartial platform for an open and honest discussion about the journey of undertaking a PhD, led by the presenters without judgement.
-
ItemInformation Systems Modeling: Playing with the Interplay Between Data and Processes(Springer, 2020)Data and processes go hand-in-hand in information systems but are often mod- eled, validated, and veri_ed separately in the systems' design phases. Designers of information systems often proceed by ensuring that database tables satisfy normal forms, and process models capturing the dynamics of the intended infor- mation manipulations are deadlock and livelock free. However, such an approach is not su_cient, as perfect data and process designs assessed in isolation can, indeed, induce faults when combined in the end system. In this tutorial, we demonstrate our recent approach to modeling and veri- _cation of models of information systems in three parts. Firstly, we present our Information Systems Modeling Language (ISML) for describing information and process constraints and the interplay between these two types of constraints [1,2]. Secondly, we demonstrate Information Systems Modeling Suite (ISM Suite) [3], an integrated environment for developing, simulating, and analyzing models of information systems described in ISML, released under an open-source license 3. In this part, using our tools, we show several example pitfalls at the level of in- formation and process interplay. Finally, we discuss current and future research directions that aim at strengthening the theoretical foundations and practical aspects of our approach to the design of information systems.
-
ItemNo Preview AvailableDesigning Interactions for the Ageing Populations - Addressing Global Challenges(ACM, 2020-04-25)We are concurrently witnessing two significant shifts: digital devices are becoming ubiquitous, and older people are becoming a very large demographic group. However, despite the recent increase in related CHI publications, older adults continue to be underrepresented in HCI research as well as commercially. Therefore, the overarching aim of this workshop is to increase the momentum for such research within CHI and related fields such as gerontechnology. For this, we plan to create a space for discussing and sharing principles and strategies to design interactions and evaluate user interfaces (UI) for the ageing population. We thus welcome contributions of empirical studies, theories, design, and evaluation of UIs for older adults. Building on the success of last two year's workshops, we aim to grow the community of CHI researchers across borders interested in this topic by fostering a space to exchange results, methods, approaches, and ideas from research on interactive applications in support of older adults that are reflective of international diversity that is representative of CHI.
-
ItemStrike a Pose: Gender and the Public and Private Performance of Magazine Reading(ACM, 2020-08)The study of reading has a long history in the digital library community, but one issue that has been largely ignored is gender. Gender is known to play a significant role in the acquisition, reading and use of print material. However, there it is unknown to what degree the influence of reading norms carries into digital reading. In this paper we examine the differences in the readership of a variety of magazines, between their print and electronic editions. The results reveal that digital reading is, in general, less gender-conforming than print reading. However, it also appears that consumption of digital editions on mobile phones reverts towards the gender stereotypes found in print. Together, this data serves to demonstrate that digital library services, including search engines, should consider the risk of reinforcing gender stereotypes that occur when reading is a public performance, and entrenching those biases when reading is done privately
-
ItemA learning based approach to predict shortest-path distances(Open Proceedings, 2020-01-01)Shortest-path distances on road networks have many applications such as finding nearest places of interest (POI) for travel recommendations. To compute a shortest-path distance, traditional approaches traverse the road network to find the shortest path and return the path length. When the distances are needed first (e.g., to rank POIs) while the shortest paths may be computed later (e.g., after a POI is chosen), one may precompute and store the distances, and answer distance queries by simple lookups. This approach, however, falls short in the worst-cast space cost – O(n2) for n vertices even with various optimizations. To address these limitations, we propose to learn an embedding for every vertex that preserves its distances to the other vertices. We then train a multi-layer perceptron (MLP) to predict the distance between two vertices given their embeddings. We thus achieve fast distance predictions without a high space cost. Experimental results on real road networks confirm these advantages. Meanwhile, our approach is up to 97% more accurate than the state-of-the-art approaches for distance predictions.