From Word Embeddings To Document Distances

812 indexed citations

Abstract

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About

This paper, published in 2015, received 812 indexed citations. Written by Matt J. Kusner, Yu Sun, Nicholas Kolkin and Kilian Q. Weinberger covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (628 citations), Information Systems (183 citations) and Computer Vision and Pattern Recognition (133 citations). Published in PolyPublie (École Polytechnique de Montréal).

In The Last Decade

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Countries where authors are citing From Word Embeddings To Document Distances

Specialization
Citations

This map shows the geographic impact of From Word Embeddings To Document Distances. 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 From Word Embeddings To Document Distances with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites From Word Embeddings To Document Distances more than expected).

Fields of papers citing From Word Embeddings To Document Distances

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of From Word Embeddings To Document Distances. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the From Word Embeddings To Document Distances.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/w4847201.

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