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Rob de Groot

dblp:18/3375 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Information retrieval › document retrieval
passage retrieval
0.012000
Finding relevant passages using noun-noun compounds: coherence vs. proximity · SIGIR 2000
Information retrieval › document retrieval › text search
phrase-based retrieval
0.012000
Finding relevant passages using noun-noun compounds: coherence vs. proximity · SIGIR 2000
Information retrieval
retrieval models
0.012000
Finding relevant passages using noun-noun compounds: coherence vs. proximity · SIGIR 2000
Information retrieval
similarity search
0.012000
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
YearPublicationVenuePosition
2000 Finding relevant passages using noun-noun compounds: coherence vs. proximity
abstract
Intuitively, 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
SIGIR2