Mapping Entity Sets in News Archives Across Time
Mapping Entity Sets in News Archives Across Time
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DOI：
10.1007/s41019-019-00102-3
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发表时间：
2019-09
影响因子：
4.2
通讯作者：
Yijun Duan;A. Jatowt;S. Bhowmick;Masatoshi Yoshikawa
中科院分区：
文献类型：
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作者：
Yijun Duan;A. Jatowt;S. Bhowmick;Masatoshi Yoshikawa
我们提出了一种新的方式来利用和访问存储在新闻档案中的信息，以及一种新的风格调查的历史。我们的想法是自动生成相似的实体对给定的两组实体，一个来自过去，一个代表现在。这允许在不同时间之间执行面向实体的映射。我们介绍了一种有效的方法来解决上述任务的基础上一个简洁的整数线性规划框架。特别是，我们的模型首先进行典型性分析，以估计实体的代表性。接下来，它在两个实体集合之间构造正交变换。结果是一组典型的跨时间可比数据。我们通过定性和定量测试证明了我们的方法在纽约数据集上的有效性。
We propose a novel way of utilizing and accessing information stored in news archives as well as a new style of investigating the history. Our idea is to automatically generate similar entity pairs given two sets of entities, one from the past and one representing the present. This allows performing entity-oriented mapping between different times. We introduce an effective method to solve the aforementioned task based on a concise integer linear programming framework. In particular, our model first conducts typicality analysis to estimate entity representativeness. It next constructs orthogonal transformation between the two entity collections. The result is a set of typical across-time comparables. We demonstrate the effectiveness of our approach on the New York Times dataset through both qualitative and quantitative tests.