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Document embeddings learned on various types of n-grams for cross-topic authorship attribution

Research article (Computing, 2018) · cited 39× · AI/ML
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Document embeddings learned on various types of n-grams for cross-topic authorship attribution

Summary

Document embeddings learned on various types of n-grams for cross-topic authorship attribution is a scholarly article[1].

Key Facts

  • Document embeddings learned on various types of n-grams for cross-topic authorship attribution's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Document embeddings learned on various types of n-grams for cross-topic authorship attribution. Retrieved May 24, 2026, from https://4ort.xyz/entity/document-embeddings-learned-on-various-types-of-n-grams-for-cross-topic-authorship-attribution
MLA “Document embeddings learned on various types of n-grams for cross-topic authorship attribution.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/document-embeddings-learned-on-various-types-of-n-grams-for-cross-topic-authorship-attribution.
BibTeX @misc{4ortxyz_document-embeddings-learned-on-various-types-of-n-grams-for-cross-topic-authorship-attribution_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Document embeddings learned on various types of n-grams for cross-topic authorship attribution}}, year = {2026}, url = {https://4ort.xyz/entity/document-embeddings-learned-on-various-types-of-n-grams-for-cross-topic-authorship-attribution}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Document embeddings learned on various types of n-grams for cross-topic authorship attribution — https://4ort.xyz/entity/document-embeddings-learned-on-various-types-of-n-grams-for-cross-topic-authorship-attribution (retrieved 2026-05-24)

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