Demo Data from VLDB 2026 / reviewers in the wild / expert
Robert Book
dblp:51/6497
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1999
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Interaction techniques and input · 87% Wearable and physiological sensing · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Interaction techniques and input › text entry
mobile touch typing |
0.0 | 1 | 1999 | Non-Keyboard QWERTY Touch Typing: A Portable Input Interface for The Mobile User · CHI 1999 |
Interaction techniques and input
text entry |
0.0 | 1 | 1999 | Non-Keyboard QWERTY Touch Typing: A Portable Input Interface for The Mobile User · CHI 1999 |
Methods — techniques the papers use, named apart from their topics
language model · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1999 | Non-Keyboard QWERTY Touch Typing: A Portable Input Interface for The Mobile UserabstractUsing traditional mobile input devices results in decreased effectiveness and efficiency. To improve usability issues a portable Non-Keyboard QWERTY touch-typing paradigm that supports the mobile touch-typing user is presented and investigated. It requires negligible training time. Pressure sensors strapped to the fingertips of gloves detect which finger is depressed. A language model based on lexical and syntactic knowledge transforms the depressed finger stroke sequence into real words and sentences. Different mobile input QWERTY paradigms (miniaturised, floating and Non-Keyboard) have been compared with full-size QWERTY. Among the mobile input paradigms, the Non-Keyboard fared significantly better, both regarding character error rate and subjective ratings. Mikael Goldstein, Robert Book, Gunilla Alsiö, Silvia Tessa |
CHI | 2 |