Semantic Compositionality through Recursive Matrix-Vector Spaces

767 indexed citations

Abstract

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This paper, published in 2012, received 767 indexed citations. Written by Richard Socher, Brody Huval, Christopher D. Manning and Andrew Y. Ng covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (736 citations), Information Systems (72 citations) and Computer Vision and Pattern Recognition (66 citations). Published in Empirical Methods in Natural Language Processing.

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Countries where authors are citing Semantic Compositionality through Recursive Matrix-Vector Spaces

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This map shows the geographic impact of Semantic Compositionality through Recursive Matrix-Vector Spaces. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Semantic Compositionality through Recursive Matrix-Vector Spaces with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Semantic Compositionality through Recursive Matrix-Vector Spaces more than expected).

Fields of papers citing Semantic Compositionality through Recursive Matrix-Vector Spaces

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Semantic Compositionality through Recursive Matrix-Vector Spaces. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Semantic Compositionality through Recursive Matrix-Vector Spaces.

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This paper is also available at doi.org/w7113710.

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