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Dae-Ho Baek

dblp:91/4083 · DBLP profile ↗
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1ranked-venue papers
1as 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 · 1 first-author

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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › query formulation
boolean query formulation
0.012000
Latent semantic indexing model for boolean query formulation · SIGIR 2000
Information retrieval › retrieval models › latent semantic models
latent semantic indexing
0.012000
Latent semantic indexing model for boolean query formulation · SIGIR 2000
Information retrieval
retrieval models
0.012000
Latent semantic indexing model for boolean query formulation · SIGIR 2000

Methods — techniques the papers use, named apart from their topics

singular value decomposition · 0.0
YearPublicationVenuePosition
2000 Latent semantic indexing model for boolean query formulation
abstract
A new model named Boolean Latent Semantic Indexing model based on the Singular Value Decomposition and Boolean query formulation is introduced. While the Singular Value Decomposition alleviates the problems of lexical matching in the traditional information retrieval model, Boolean query formulation can help users to make precise representation of their information search needs. Retrieval experiments on a number of test collections seem to show that the proposed model achieves substantial performance gains over the Latent Semantic Indexing model.
Dae-Ho Baek, Heui-Seok Lim, Hae-Chang Rim
SIGIR1