Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). A novel embedding approach to learn word vectors by weighting semantic relations: SemSpace. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-novel-embedding-approach-to-learn-word-vectors-by-weighting-semantic-relations-semspace
MLA“A novel embedding approach to learn word vectors by weighting semantic relations: SemSpace.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-novel-embedding-approach-to-learn-word-vectors-by-weighting-semantic-relations-semspace.
BibTeX@misc{4ortxyz_a-novel-embedding-approach-to-learn-word-vectors-by-weighting-semantic-relations-semspace_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A novel embedding approach to learn word vectors by weighting semantic relations: SemSpace}}, year = {2026}, url = {https://4ort.xyz/entity/a-novel-embedding-approach-to-learn-word-vectors-by-weighting-semantic-relations-semspace}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A novel embedding approach to learn word vectors by weighting semantic relations: SemSpace — https://4ort.xyz/entity/a-novel-embedding-approach-to-learn-word-vectors-by-weighting-semantic-relations-semspace (retrieved 2026-05-24)
