Less is Less: When Are Snippets Insufficient for Human vs Machine Relevance Estimation?. (arXiv:2201.08721v1 [cs.IR])

Web: http://arxiv.org/abs/2201.08721

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 …

arxiv human machine