Demo Data from EDBT 2026 / reviewers in the wild / expert
Joey Jan
dblp:90/8024
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1Applied, interdisciplinary, general and emerging 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.
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval › interactive information retrieval › search interaction
collaborative search |
0.1 | 1 | 2010 | Rants: a framework for rank editing and sharing in web search · WWW 2010 |
Information retrieval › ranking › result ranking
search result ranking |
0.1 | 1 | 2010 | Rants: a framework for rank editing and sharing in web search · WWW 2010 |
Methods — techniques the papers use, named apart from their topics
rank aggregation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Rants: a framework for rank editing and sharing in web searchabstractWith a Wiki-like search interface, users can edit ranks of search results and share the edits with the rest of the world. This is an effective way of personalization, as well as a practice of mass collaboration that allows users to vote for ranking and improve search performance. Currently, there are several ongoing experimentation efforts from the industry, e.g., SearchWiki by Google and U Rank by Microsoft. Beyond that, there is little published research on this new search paradigm. In this paper, we make an effort to establish a framework for rank editing and sharing in the context of web search, where we identify fundamental issues and propose principled solutions. Comparing to existing systems, for rank editing, our framework allows users to specify not only relative, but also absolute preferences. For edit sharing, our framework provides enhanced flexibility, allowing users to select arbitrarily aggregated views. In addition, edits can be shared among similar queries. We present a prototype system Rants, that implements the framework and provides search services through the Google web search API. Byron J. Gao, Joey Jan |
WWW | 2 |