Proceedings of the 14th international conference on Intelligent user interfaces
Bibliographic record
Abstract
The 2009 International Conference on Intelligent User Interfaces (IUI 2009) is the 14th such meeting since the first international conference in 1997. This series of annual conferences is the principal international forum for the presentation and discussion of outstanding research and applications involving intelligent user interfaces, a field at the intersection of Human-Computer Interaction and Artificial Intelligence. IUI focuses on interfaces that incorporate machine learning and artificial intelligence techniques. The interests and creative outlets of the community span a wide range of topics reflected in this year's meeting. These include automatic summarization techniques, recommendations and intelligent Web systems, intelligent information and knowledge management, example and demonstration based interfaces, novel approaches to input and output, mobile interaction, intelligent assistants and visualization and designer tools. This year's submitted papers came from all continents. In addition, both the program committee and submitted papers included members from industry and academia. This year's IUI conference counted with 134 long papers and 59 short papers submitted. Of the papers submitted, this program includes 35 long papers (26%) and 21 short papers, including long papers accepted as short papers. The papers program is complemented by the always popular Posters and Demonstrations session where authors of accepted short papers can showcase their work and where many published authors present live demos of their systems. This year's eight demonstrations will be presented during the Poster session. Intelligent User Interfaces are increasingly becoming a reality in our daily interactions with computers. Therefore, this year's invited speakers represent an interesting mix between industry and academia: Professor Trevor Darrell, from ICSI and University of Berkeley, Dr Jun Rekimoto from Sony Labs and University of Tokyo, and Dr. Alon Halvey, from Google. Seven workshops, each a full day, will also take place at IUI this year: Common Sense and Intelligent User Interfaces 2009: Story Understanding and Generation for Context-Aware Interface Design; Multimodal Interfaces for Automotive Applications (MIAA); Human Interaction with Intelligent & Networked Systems; Users' Preferences Regarding Intelligent User Interfaces: Differences Among Users and Changes Over Time; Visual Interfaces to the Social and the Semantic Web; Sketch Recognition and Model Driven Development of Advanced User Interfaces (MDDAUI 2009). Interestingly, this year's IUI has a record number of workshops, counterbalanced by a lack of tutorials. Perhaps this signifies a change of focus in the IUI community?
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.094 | 0.050 |
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".