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Title: Mapping entity sets in news archives across time
Authors: Duan, Yijun
Jatowt, Adam
Bhowmick, Sourav S.
Yoshikawa, Masatoshi
Keywords: Engineering::Computer science and engineering
Issue Date: 2019
Source: Duan, Y., Jatowt, A., Bhowmick, S. S., & Yoshikawa, M. (2019). Mapping entity sets in news archives across time. Data Science and Engineering, 4(3), 208-222. doi:10.1007/s41019-019-00102-3
Journal: Data Science and Engineering
Abstract: 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.
ISSN: 2364-1185
DOI: 10.1007/s41019-019-00102-3
Rights: © 2019 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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