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Philip J. Cowans

dblp:84/3905 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2004
—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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval
retrieval models
0.012004
Information retrieval using hierarchical dirichlet processes · SIGIR 2004
Information retrieval › retrieval models
term weighting
0.012004
Information retrieval using hierarchical dirichlet processes · SIGIR 2004
Information retrieval › retrieval models › term weighting
TF-IDF
0.012004
Information retrieval using hierarchical dirichlet processes · SIGIR 2004
Information retrieval › retrieval models › term weighting
document length normalization
0.012004
Information retrieval using hierarchical dirichlet processes · SIGIR 2004

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

hierarchical dirichlet process · 0.0bayesian modeling · 0.0
YearPublicationVenuePosition
2004 Information retrieval using hierarchical dirichlet processes
abstract
An information retrieval method is proposed using a hierarchical Dirichlet process as a prior on the parameters of a set of multinomial distributions. The resulting method naturally includes a number of features found in other popular methods. Specifically, tf.idf-like term weighting and document length normalisation are recovered. The new method is compared with Okapi BM-25 [3] and the Twenty-One model [1] on TREC data and is shown to give better performance.
Philip J. Cowans
SIGIR1