Demo Data from EDBT 2026 / reviewers in the wild / expert
Josh Creter
dblp:25/608
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1997
—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.
| Databases, data mining, and information retrieval
1 paper |
Recommender systems · 87% Web and social media mining · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Recommender systems
collaborative filtering |
0.0 | 1 | 1997 | Building Task-Specific Interfaces to High Volume Conversational Data · CHI 1997 |
Recommender systems
resource recommendation |
0.0 | 1 | 1997 | Building Task-Specific Interfaces to High Volume Conversational Data · CHI 1997 |
Methods — techniques the papers use, named apart from their topics
text parsing · 0.0tallying · 0.0classification · 0.0abstraction · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1997 | Building Task-Specific Interfaces to High Volume Conversational DataabstractAs people participate in the thousands of global conversations that comprise Usenet news, one thing they do is post their opinions of web resources. Phoaks is a collaborative filtering system that continuously parses, classifies, abstracts and tallies those opinions. About 3,500 users per day consult Phoaks web pages that reflect the results. Phoaks also features a general architecture for building similar collaborative filtering interfaces to conversational data. We report here on the Phoaks resource recommendation interface, the architecture, and the issues and experience that make up its rationale. Keywords human-computer interaction, human interface, computersupported cooperative work, organizational computing, social filtering, collaborative filtering, data mining, Loren G. Terveen, William C. Hill, Brian Amento, David W. McDonald, Josh Creter |
CHI | 5 |