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Query expansion
Known as:
Automatic query reformulation
, QE
Query expansion (QE) is the process of reformulating a seed query to improve retrieval performance in information retrieval operations.In the context…
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Related topics
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Computer science
Document retrieval
Google Search
Human–computer information retrieval
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Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
The Escape from Balance Sheet Recession and the QE Trap : A Hazardous Road for the World Economy , Singapore ( 320 pages , hardcover , Wiley , ISBN 978-1119-02812-3 )
2016
Corpus ID: 145043082
Richard Koo, the chief economist at a leading securities house, became a widely known author with the publication of his 2008…
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2014
2014
Document-level translation quality estimation: exploring discourse and pseudo-references
Carolina Scarton
,
Lucia Specia
European Association for Machine Translation…
2014
Corpus ID: 6040902
Predicting the quality of machine translations is a challenging topic. Quality estimation (QE) of translations is based on…
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Highly Cited
2011
Highly Cited
2011
Automatic Enrichment of Semantic Relation Network and Its Application to Word Sense Disambiguation
Myunggwon Hwang
,
Chang Choi
,
Pankoo Kim
IEEE Transactions on Knowledge and Data…
2011
Corpus ID: 14556411
The most fundamental step in semantic information processing (SIP) is to construct knowledge base (KB) at the human level; that…
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2009
2009
LDSR: Materialized Reason-able View to the Web of Linked Data
A. Kiryakov
,
Damyan Ognyanoff
,
Ruslan Velkov
,
Zdravko Tashev
,
Ivan Peikov
RuleML Challenge
2009
Corpus ID: 1088993
LDSR is a collection of datasets from the Linked Open Data (LOD) W3C community project, which have been selected and refined for…
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Highly Cited
2006
Highly Cited
2006
Question Answering with LCC's CHAUCER at TREC 2006
Andrew Hickl
,
Kirk Roberts
,
+4 authors
John Williams
Text Retrieval Conference
2006
Corpus ID: 1436801
C HAUCER is a Q/A system developed for (a) combining several strategies for modeling the target of a series of questions and (b…
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2004
2004
Extending and Enriching WordNet with OntoLearn
P. Velardi
,
Roberto Navigli
,
A. Cucchiarelli
,
Francesca Neri
2004
Corpus ID: 9861360
OntoLearn is a system for word sense disambiguation, used to automat- ically enrich WordNet with domain concepts and to…
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Highly Cited
2004
Highly Cited
2004
TRECVID 2004 Experiments in Dublin City University
E. Cooke
,
Paul Ferguson
,
+13 authors
Peter Wilkins
TREC Video Retrieval Evaluation
2004
Corpus ID: 12025192
In this paper, we describe our experiments for TRECVID 2004 for the Search task. In the interactive search task, we developed two…
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2004
2004
Question Answering using Sentence Parsing and Semantic Network Matching
Sven Hartrumpf
Conference and Labs of the Evaluation Forum
2004
Corpus ID: 11454893
The paper describes a question answering system for German called InSicht. All documents in the system are analyzed by a…
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2002
2002
SICS at CLEF 2002: Automatic Query Expansion using Random Indexing
Magnus Sahlgren
,
Jussi Karlgren
,
Rickard Cöster
,
Timo Järvinen
Conference and Labs of the Evaluation Forum
2002
Corpus ID: 26632181
Vector space techniques can be used for extracting semantically similar words from the co-occurrence statistics of words in large…
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Highly Cited
1992
Highly Cited
1992
Effectiveness of query expansion in ranked-output document retrieval systems
F. Ç. Ekmekçioglu
,
A. Robertson
,
P. Willett
Journal of information science
1992
Corpus ID: 38531454
This paper reports an evaluation of three methods for the expansion of natural language queries in ranked-out put retrieval…
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