History by Diversity: Helping Historians search News Archives
History by Diversity: Helping Historians search News Archives
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多样性历史：帮助历史学家搜索新闻档案
DOI：
10.1145/2854946.2854959
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Avishek Anand
中科院分区：
文献类型：
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作者：
Jaspreet Singh;W. Nejdl;Avishek Anand
像报纸档案这样的纵向语料库对历史研究具有巨大的价值，时间作为历史学家的一个重要因素，强烈地影响着他们在这些档案中的搜索行为。在搜索一段时间内发表的文章时，一个关键的偏好是检索涵盖重要时间点的重要方面的文档，这与标准搜索行为不同。为了支持这种搜索策略，我们引入了历史查询意图的概念来显式地建模历史学家的搜索任务，并定义了新闻档案的方面时间多样化问题。我们提出了一种新的算法HistDiv，它基于历史学家的信息寻找行为明确地建模方面和重要的时间窗口。通过结合基于出版时间和时间表达式的时间先验，我们在方面和时间维度上实现了多样化。我们通过构建一个基于纽约时报集合的测试集合来测试我们的方法，该集合具有30个手动评估的历史意图查询的工作负载。我们发现HistDiv在子主题召回方面优于所有竞争对手，但精度略有下降。我们还提供了一项定性用户研究的结果，以确定精确度的下降是否对用户体验有害。我们的结果显示，用户仍然更喜欢HistDiv的排名。
Longitudinal corpora like newspaper archives are of immense value to historical research, and time as an important factor for historians strongly influences their search behaviour in these archives. While searching for articles published over time, a key preference is to retrieve documents which cover the important aspects from important points in time which is different from standard search behavior. To support this search strategy, we introduce the notion of a Historical Query Intent to explicitly model a historian's search task and define an aspect-time diversification problem over news archives. We present a novel algorithm, HistDiv, that explicitly models the aspects and important time windows based on a historian's information seeking behavior. By incorporating temporal priors based on publication times and temporal expressions, we diversify both on the aspect and temporal dimensions. We test our methods by constructing a test collection based on The New York Times Collection with a workload of 30 queries of historical intent assessed manually. We find that HistDiv outperforms all competitors in subtopic recall with a slight loss in precision. We also present results of a qualitative user study to determine wether this drop in precision is detrimental to user experience. Our results show that users still preferred HistDiv's ranking.