Understand
Recent work in Information Retrieval (IR) using Deep Learning models has yielded state of the art results on a variety of IR tasks.
- Deep neural networks (DNN) are capable of learning ideal representations of data during the training process, removing the need for independently extracting features.
- However, the structures of these DNNs are often tailored to perform on specific datasets.
- In addition, IR tasks deal with text at varying levels of granularity from single factoids to documents containing thousands of words.
Built on
Learning to rank answers on large online qa collections
M. Surdeanu, M. Ciaramita, and H. Zaragoza · 2008
Earlier work this paper cites.
Statistical language models for information retrieval
C. Zhai · 2008
Earlier work this paper cites.
Learning deep structured semantic models for web search using clickthrough data
P.-S. Huang, X. He, J. Gao, L. Deng, A. Acero, and L. Heck · 2013
Earlier work this paper cites.
Distributed representations of sentences and documents
Q. V. Le and T. Mikolov · 2014
Earlier work this paper cites.
Semantic modelling with long-short-term memory for information retrieval
H. Palangi, L. Deng, Y. Shen, J. Gao, X. He, J. Chen, X. Song, and R. Ward · 2014
Earlier work this paper cites.
Similar
A latent semantic model with convolutional-pooling structure for information retrieval
Y. Shen, X. He, J. Gao, L. Deng, and G. Mesnil · 2014
Cited alongside, same era.
Applying Deep Learning to Answer Selection: A Study and An Open Task
M. Feng, B. Xiang, M. R. Glass, L. Wang, and B. Zhou · 2015
Cited alongside, same era.
Convolutional neural network architectures for matching natural language sentences
B. Hu, Z. Lu, H. Li, and Q. Chen · 2015
Cited alongside, same era.
Learning to rank short text pairs with convolutional deep neural networks
A. Severyn and A. Moschitti · 2015
Cited alongside, same era.
Lstm-based deep learning models for non-factoid answer selection
M. Tan, B. Xiang, and B. Zhou · 2015
Cited alongside, same era.
A recurrent neural network based answer ranking model for web question answering
D. Wang and E. Nyberg
Cited in the paper.
A recurrent neural network based answer ranking model for web question answering
D. Wang and E. Nyberg
Cited in the paper.
Then
Monolingual and cross-lingual information retrieval models based on (bilingual) word embeddings
I. Vulić and M.-F. Moens · 2015
Later among the works it cites.
ABCNN: attention-based convolutional neural network for modeling sentence pairs
W. Yin, H. Schütze, B. Xiang, and B. Zhou · 2015
Later among the works it cites.
C. N. dos Santos, M. Tan, B. Xiang, and B. Zhou · 2016
Closest in time.
Deep sentence embedding using long short-term memory networks: Analysis and application to information retrieval
H. Palangi, L. Deng, Y. Shen, J. Gao, X. He, J. Chen, X. Song, and R. K. Ward · 2016
Closest in time.
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