阅读位置是基线：个性化高亮预测的时间顺序评估
原标题：Reading Position Is the Baseline to Beat: A Time-Ordered Evaluation of Personalised Highlight Prediction
AI 摘要
该论文在社交高亮平台上进行时间顺序评估，提出阅读位置是文档内个性化高亮预测必须超越的基线。实验显示，仅根据读者首次高亮位置排序句子，预测下一次高亮的Hit@5达47%，远超流行度（26%）和两种相似度方法（29%）。但针对所有后续高亮时，位置基线输给流行度，而按距离衰减的流行度基线表现最佳。论文强调个性化评估需按时间顺序并对照阅读位置，且相似度方法的增益可能仅反映位置而非偏好。
正文节选
Reading Position Is the Baseline to Beat: A Time-Ordered Evaluation of Personalised Highlight Prediction Abstract A reader’s first highlights on a page are the cheapest personal signal a reading product has. The natural plan is to suggest what similar earlier readers marked, and to judge the result against popularity. We argue that the baseline to beat is reading position. In a time-ordered evaluation on one social highlighting platform (7,343 reader-page pairs on 1,511 pages after one highlight