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Less is Less: When Are Snippets Insufficient for Human vs Machine Relevance Estimation?. (arXiv:2201.08721v1 [cs.IR])
Jan. 24, 2022, 2:10 a.m. | Gabriella Kazai, Bhaskar Mitra, Anlei Dong, Nick Craswell, Linjun Yang
cs.LG updates on arXiv.org arxiv.org
Traditional information retrieval (IR) ranking models process the full text
of documents. Newer models based on Transformers, however, would incur a high
computational cost when processing long texts, so typically use only snippets
from the document instead. The model's input based on a document's URL, title,
and snippet (UTS) is akin to the summaries that appear on a search engine
results page (SERP) to help searchers decide which result to click. This raises
questions about when such summaries are sufficient …
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