量化对话答案背后最少需多少查询动作才能还原
Answer-Reconstruction Search Density: Measuring the Query and Source Work Compressed by Conversational Answers
- 提出搜索密度指标，衡量答案压缩的查询与来源工作量
- 在固定重建策略下，计算支持答案单元所需的最少查询次数
- 适用于评估对话系统检索效率，适合研究人机交互与搜索优化
对话系统可将一系列网页查询、结果查看和源文件对比压缩成单一合成答案。现有检索评估指标关注排序质量、用户努力或事实支持，但无法量化一个完成答案所代表的最小传统搜索工作量。本文定义了答案重构搜索密度（ARSD）：在固定且过时的重建策略下，支持目标比例原子可检索答案单元所需的最少不同查询动作数。并引入平行页密度度量，分离查询压缩与源压缩的影响。
原文摘要 · Abstract (English)
Conversational systems can collapse a visible sequence of web queries, result inspections, and source comparisons into a single synthesized answer. Existing retrieval metrics evaluate ranking, effort, or factual support, but they do not quantify the minimum conventional search work represented by a completed answer. We define answer-reconstruction search density (\ARSD): the minimum number of distinct query actions required, under a fixed and dated reconstruction policy, to support a target share of atomic retrievable answer units. A parallel page-density measure separates query compression from source compression.
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