Proceedings of the 10th asia pacific conference on Computer human interaction
Bibliographic record
Abstract
It is our great pleasure to welcome you to APCHI 2012, the 10th Asia-Pacific Conference on Computer-Human Interaction held on 28--31 August in Matsue-city, Shimane, Japan. Following the success of earlier APCHI conferences in Singapore (1996, 2000), Australia (1997), Japan (1998), China (2002), New Zealand (2004), Taiwan (2006), Korea (2008), and Indonesia (2010), the 10th APCHI has brought researchers and practitioners together from academia and industry and has provided an excellent opportunity to exchange ideas and information related to human-computer interaction and related areas in computer and communication technologies as well as human and social sciences. APCHI has been an important forum for scholars and practitioners in the Asia-Pacific region for the latest challenges and developments in Human-Computer Interaction (HCI). APCHI 2012 is co-sponsored by the Human- Centered Design organization (HCD-Net, Japan) and ACM SIGCHI. APCHI 2012 is the memorable 10th event in the APCHI conference series. During the last 16 years, the field of HCI has been progressing at a rapid pace. Computers and communication technologies have become an indispensable part of infrastructure in our daily life. With these technologies, we share experiences with loved ones, connect with old school friends, broadcast homemade videos, and exchange personal opinions among a loosely coupled community. We learn new knowledge, create business documents, trade stocks, and buy books and music. Nevertheless, important problems remain unsolved, including the tension between usability and user experience, cutting-edge technology and universal access, enjoyment and office work, natural home settings and controlled laboratory settings, and creative work and labor. For this reason, APCHI 2012 set Reflect, Discover and Innovate as the conference theme. We reflect upon the past experiences in HCI, discover new findings from present activities, and innovate the quality of our future life. To discuss the theme, APCHI 2012 invited four keynote speakers: Dr. Shumin Zhai of Google Research, Professor Yuichiro Anzai of Japan Society for the Promotion of Science / Keio University, Professor Marc Hassenzahl of Folkwang University, and Professor Asako Kimura of Ritsumeikan University. We also have workshops and tutorials before the main conference. APCHI 2012 attracted a total of 155 paper submissions. The review process involved a double blindreview with a minimum of two reviewers, a meta-reviewer from the International Associated Program Committee members, and program committee members who met in Tokyo, Japan on 26-28 April, 2012. Among the submissions, 41 papers were accepted as long talks (acceptance rate of 26.5%) and 48 papers were accepted as short talks (acceptance rate of 30%). This proceedings volume presents the 36 technica contributions as long talks, which were offered from many different countries and regions including Australia, Austria, Belgium, Canada, China, Denmark, France, Germany, Japan, Korea, Malaysia, bSingapore, and the USA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.215 | 0.131 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".