扩充广告搜索结果页数据，实现元素级行为分析。
AllSERP: Exhaustive Per-Element Enrichment of the Versatile AdSERP Dataset
- 通过图像与网页解析，精准标注每类页面元素边界。
- 点击归因率达91.7%，覆盖98%以上页面元素行为数据。
- 适合研究搜索结果点击、注视及用户行为的细分分析者。
我们发布AllSERP，对原始的AdSERP商业意图搜索结果页（SERP）语料库进行类型化区域（AOI）和元素级行为增强。AdSERP包含2,776次全屏截图、真实谷歌搜索页的HTML、150 Hz Gazepoint眼动追踪、evtrack鼠标轨迹、滚动和瞳孔信号，但其边界框仅覆盖广告区域（占可归因点击的15.5%）。AllSERP通过截图锚定的计算机视觉技术，添加像素级有机内容与组件边界框；利用HTML解析器赋予十三种元素类型语义标签；引入跨结果间隙填充模式（typed_gapfill）；并实现X+Y点击归因，使归因率提升至91.7%的同时在试验级别标记未归因部分。阶段C的广告-非广告划分与原广告矩形完全一致（38,250次分类无分歧）。我们提供完整处理流程、每条试验的JSON文件、语料库CSV以及浏览器重播查看器，所有内容均可从AdSERP Zenodo资源中复现。该发布支持元素级点击、凝视、回归及首屏以上分析，突破了原始广告-有机划分的局限。
原文摘要 · Abstract (English)
We release AllSERP, a typed AOI and per-element behavioral enrichment of the AdSERP commercial-intent SERP corpus [4]. AdSERP ships 2,776 trials of full-page screenshots, captured SERP HTML, 150 Hz Gazepoint eye tracking, evtrack mouse telemetry, scroll, and pupil signals against real Google SERPs collected before AI Overviews -- but its bounding boxes cover only ad surfaces (15.5 % of attributable clicks). AllSERP adds pixel-accurate organic and widget bboxes via screenshot-anchored CV, semantic types across thirteen element types via an HTML parser, an inter-result gap-fill flavor (typed_gapfill), and X+Y click attribution that reaches 91.7 % of the corpus while flagging the rest at trial level. The Phase C ad-vs-non-ad partition is internally consistent with the shipped ad rectangles (0 disagreements across 38,250 classifications). We ship the pipeline, per-trial JSONs, a corpus CSV, and a browser-based replay viewer; everything is reproducible from the AdSERP Zenodo volume. The release enables per-element click, fixation, regression, and above-fold analyses that the shipped ads-vs-organic split could not resolve.
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