PACRR: A position-aware neural IR model for relevance matching
In order to adopt deep learning for information retrieval, models are needed that can capture
all relevant information required to assess the relevance of a document to a given user …
all relevant information required to assess the relevance of a document to a given user …
[PDF][PDF] PACRR: A Position-Aware Neural IR Model for Relevance Matching
K Hui, A Yates, K Berberich, G de Melo - khui.github.io
PACRR: A Position-Aware Neural IR Model for Relevance Matching Page 1 PACRR: A
Position-Aware Neural IR Model for Relevance Matching Kai Hui1, Andrew Yates1, Klaus …
Position-Aware Neural IR Model for Relevance Matching Kai Hui1, Andrew Yates1, Klaus …
[PDF][PDF] PACRR: A Position-Aware Neural IR Model for Relevance Matching
K Hui, A Yates, K Berberich, G de Melo - scholar.archive.org
In order to adopt deep learning for information retrieval, models are needed that can capture
all relevant information required to assess the relevance of a document to a given user …
all relevant information required to assess the relevance of a document to a given user …
PACRR: A Position-Aware Neural IR Model for Relevance Matching
K Hui, A Yates, K Berberich… - Proceedings of the 2017 …, 2017 - aclanthology.org
In order to adopt deep learning for information retrieval, models are needed that can capture
all relevant information required to assess the relevance of a document to a given user …
all relevant information required to assess the relevance of a document to a given user …
PACRR: A position-aware neural IR model for relevance matching
K Hui, A Yates, K Berberich… - 2017 Conference on …, 2017 - researchwithrutgers.com
In order to adopt deep learning for information retrieval, models are needed that can capture
all relevant information required to assess the relevance of a document to a given user …
all relevant information required to assess the relevance of a document to a given user …
[PDF][PDF] PACRR: A Position-Aware Neural IR Model for Relevance Matching
K Hui, A Yates, K Berberich, G de Melo - pdfs.semanticscholar.org
PACRR: A Position-Aware Neural IR Model for Relevance Matching Page 1 PACRR: A
Position-Aware Neural IR Model for Relevance Matching Kai Hui1, Andrew Yates1, Klaus …
Position-Aware Neural IR Model for Relevance Matching Kai Hui1, Andrew Yates1, Klaus …
[PDF][PDF] PACRR: A Position-Aware Neural IR Model for Relevance Matching
K Hui, A Yates, K Berberich, G de Melo - gerard.demelo.org
In order to adopt deep learning for information retrieval, models are needed that can capture
all relevant information required to assess the relevance of a document to a given user …
all relevant information required to assess the relevance of a document to a given user …
[PDF][PDF] PACRR: A Position-Aware Neural IR Model for Relevance Matching
K Hui, A Yates, K Berberich, G de Melo - researchgate.net
In order to adopt deep learning for information retrieval, models are needed that can capture
all relevant information required to assess the relevance of a document to a given user …
all relevant information required to assess the relevance of a document to a given user …
PACRR: A Position-Aware Neural IR Model for Relevance Matching
K Hui, A Yates, K Berberich, G de Melo - arXiv preprint arXiv …, 2017 - pure.mpg.de
In order to adopt deep learning for information retrieval, models are needed that can capture
all relevant information required to assess the relevance of a document to a given user …
all relevant information required to assess the relevance of a document to a given user …
PACRR: A Position-Aware Neural IR Model for Relevance Matching
K Hui, A Yates, K Berberich, G de Melo - arXiv e-prints, 2017 - ui.adsabs.harvard.edu
In order to adopt deep learning for information retrieval, models are needed that can capture
all relevant information required to assess the relevance of a document to a given user …
all relevant information required to assess the relevance of a document to a given user …