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Word embedding, specially with its recent developments, promises a quantification of the similarity between terms.
A language modeling approach to information retrieval
J. M. Ponte and W. B. Croft · 1998
Earlier work this paper cites.
Information Retrieval As Statistical Translation
A. Berger and J. Lafferty · 1999
Earlier work this paper cites.
A Study of Smoothing Methods for Language Models Applied to Ad Hoc Information Retrieval
C. Zhai and J. Lafferty · 2001
Earlier work this paper cites.
Alternatives to bpref
T. Sakai · 2007
Earlier work this paper cites.
Filaments of meaning in word space
J. Karlgren, A. Holst, and M. Sahlgren · 2008
Earlier work this paper cites.
Exemplar-based models for word meaning in context
K. Erk and S. Padó · 2010
Earlier work this paper cites.
Estimation of Statistical Translation Models Based on Mutual Information for Ad Hoc Information Retrieval
M. Karimzadehgan and C. Zhai · 2010
Earlier work this paper cites.
An evaluation of corpus-driven measures of medical concept similarity for information retrieval
B. Koopman, G. Zuccon, P. Bruza, L. Sitbon, and M. Lawley · 2012
Earlier work this paper cites.
Efficient estimation of word representations in vector space
T. Mikolov, K. Chen, G. Corrado, and J. Dean · 2013
Earlier work this paper cites.
Don’t count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors
M. Baroni, G. Dinu, and G. Kruszewski · 2014
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Semantic topology
J. Karlgren, M. Bohman, A. Ekgren, G. Isheden, E. Kullmann, and D. Nilsson · 2014
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Glove: Global vectors for word representation
J. Pennington, R. Socher, and C. D. Manning · 2014
Cited alongside, same era.
Navigating the semantic horizon using relative neighborhood graphs, 2015
A. Cuba Gyllensten and M. Sahlgren · 2015
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Word Embedding based Generalized Language Model for Information Retrieval
D. Ganguly, D. Roy, M. Mitra, and G. J. Jones · 2015
Cited alongside, same era.
Context-and content-aware embeddings for query rewriting in sponsored search
M. Grbovic, N. Djuric, V. Radosavljevic, F. Silvestri, and N. Bhamidipati · 2015
Improving distributional similarity with lessons learned from word embeddings
O. Levy, Y. Goldberg, and I. Dagan · 2015
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Exploring session context using distributed representations of queries and reformulations
B. Mitra · 2015
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On the use of statistical semantics for metadata-based social image retrieval
N. Rekabsaz, R. Bierig, B. Ionescu, A. Hanbury, and M. Lupu · 2015
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Evaluation methods for unsupervised word embeddings
T. Schnabel, I. Labutov, D. Mimno, and T. Joachims · 2015
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Learning to rank short text pairs with convolutional deep neural networks
A. Severyn and A. Moschitti · 2015
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Evaluation of word vector representations by subspace alignment
Y. Tsvetkov, M. Faruqui, W. Ling, G. Lample, and C. Dyer · 2015
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Cited alongside, same era.
Specializing word embeddings for similarity or relatedness
D. Kiela, F. Hill, and S. Clark · 2015
Cited alongside, same era.
So similar and yet incompatible: Toward automated identification of semantically compatible words
G. Kruszewski and M. Baroni · 2015
Cited alongside, same era.
Medical semantic similarity with a neural language model
L. De Vine, G. Zuccon, B. Koopman, L. Sitbon, and P. Bruza
Cited in the paper.
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Monolingual and cross-lingual information retrieval models based on (bilingual) word embeddings
I. Vulić and M.-F. Moens · 2015
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Integrating and evaluating neural word embeddings in information retrieval
G. Zuccon, B. Koopman, P. Bruza, and L. Azzopardi · 2015
Later among the works it cites.