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Ben Johnson-Laird

dblp:11/1856 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1995
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Databases, 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
2 papers
Information retrieval · 86% Data integration and cleaning · 14%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval
distributed information retrieval		 0.021995
Learning Collection Fusion Strategies · SIGIR 1995
Learning Collection Fusion Strategies for Information Retrieval · ICML 1995
Information retrieval › distributed information retrieval
result fusion		 0.021995
Learning Collection Fusion Strategies · SIGIR 1995
Learning Collection Fusion Strategies for Information Retrieval · ICML 1995
Information retrieval
retrieval models		 0.021995
Learning Collection Fusion Strategies · SIGIR 1995
Learning Collection Fusion Strategies for Information Retrieval · ICML 1995
Data integration and cleaning
data fusion		 0.011995
Learning Collection Fusion Strategies · SIGIR 1995

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

learning to rank · 0.0
YearPublicationVenuePosition
1995 Learning Collection Fusion Strategies for Information Retrieval
Geoffrey G. Towell, Ellen M. Voorhees, Narendra Kumar Gupta, Ben Johnson-Laird
 ICML4
1995 Learning Collection Fusion Strategies
abstract
Collectionfusion is a data fusion problem in which the results of retrieval runs on separate, autonomous document collections must be merged to produce a single, effective result.This paper explores two collection fusion techniques that learn the rmrnber of documents to retrieve from each collection using only the ranked lists of documents returned in response to past queries and those documents!relevance judgments.Retrieval experiments using the TREC test co]lection demonstrate that the effectiveness of the fusion techniques is within 10'?% of the effectiveness of a run in which the entire set of documents is treated as a single collection.
Ellen M. Voorhees, Narendra Kumar Gupta, Ben Johnson-Laird
 SIGIR3