Demo Data from VLDB 2026 / reviewers in the wild / expert
Rob de Groot
dblp:18/3375
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, 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.
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval › document retrieval
passage retrieval |
0.0 | 1 | 2000 | Finding relevant passages using noun-noun compounds: coherence vs. proximity · SIGIR 2000 |
Information retrieval › document retrieval › text search
phrase-based retrieval |
0.0 | 1 | 2000 | Finding relevant passages using noun-noun compounds: coherence vs. proximity · SIGIR 2000 |
Information retrieval
retrieval models |
0.0 | 1 | 2000 | Finding relevant passages using noun-noun compounds: coherence vs. proximity · SIGIR 2000 |
Information retrieval
similarity search |
0.0 | 1 | 2000 | Finding relevant passages using noun-noun compounds: coherence vs. proximity · SIGIR 2000 |
Methods — techniques the papers use, named apart from their topics
syntactic analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | Finding relevant passages using noun-noun compounds: coherence vs. proximityabstractIntuitively, words forming phrases are a more precise description of content than words as a sequence of keywords. Yet, evidence that phrases would be more effective for information retrieval is inconclusive. This paper isolates a neglected class of phrases, that is abundant in communication, has an established theoretical foundation, and shows promise for an effective expression of the user's information need: the noun-noun compound (NNC). In an experiment, a variety of meaningful NNCs were used to isolate relevant passages in a large and varied corpus. In a first pass, passages were retrieved based on textual proximity of the words or their semantic peers. A second pass retained only passages containing a syntactically coherent structure equivalent to the original NNC. This second pass showed a dramatic increase in precision. Preliminary results show the validity of our intuition about phrases in the special but very productive case of NNCs. Eduard Hoenkamp, Rob de Groot |
SIGIR | 2 |