Demo Data from VLDB 2026 / reviewers in the wild / expert
Keh-Chiang Yu
dblp:99/4540
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 1988
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Databases, data management, data science and information retrieval · 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 |
Collaborative and social computing · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Data models and query languages · 50% Information retrieval · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing › computer-supported cooperative work
collaborative applications |
0.0 | 1 | 1988 | Object Lens: A "Spreadsheet" for Cooperative Work · ACM Trans. Inf. Syst. 1988 |
Collaborative and social computing
cooperative work |
0.0 | 1 | 1988 | Object Lens: A "Spreadsheet" for Cooperative Work · ACM Trans. Inf. Syst. 1988 |
Information retrieval › document organization
hypertext |
0.0 | 1 | 1988 | Object Lens: A "Spreadsheet" for Cooperative Work · ACM Trans. Inf. Syst. 1988 |
Data models and query languages
object-oriented database |
0.0 | 1 | 1988 | Object Lens: A "Spreadsheet" for Cooperative Work · ACM Trans. Inf. Syst. 1988 |
Methods — techniques the papers use, named apart from their topics
semistructured objects · 0.0rule-based agents · 0.0rule-based agent · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1988 | Object Lens: A "Spreadsheet" for Cooperative WorkabstractObject Lens allows unsophisticated computer users to create their own cooperative work applications using a set of simple, but powerful, building blocks. By defining and modifying templates for various semistructured objects, users can represent information about people, tasks, products, messages, and many other kinds of information in a form that can be processed intelligently by both people and their computers. By collecting these objects in customizable folders, users can create their own displays which summarize selected information from the objects in table or tree formats. Finally, by creating semiautonomous agents, users can specify rules for automatically processing this information in different ways at different times. The combination of these primitives provides a single consistent interface that integrates facilities for object-oriented databases, hypertext, electronic messaging, and rule-based intelligent agents. To illustrate the power of this combined approach, we describe several simple examples of applications (such as task tracking, intelligent message routing, and database retrieval) that we have developed in this framework. Kum-Yew Lai, Thomas W. Malone, Keh-Chiang Yu |
ACM Trans. Inf. Syst. | 3 |
| 1987 | An investigation on the nature of decision support system software
Michael Szu-Yuan Wang, Keh-Chiang Yu |
Decis. Support Syst. | 2 |
| 1982 | An empirical study of a CDC 844-41 disk subsystem
J. William Atwood, Alexander MacLeod, Keh-Chiang Yu |
Perform. Evaluation | 3 |