This paper proposes a novel approach to retrieve news articles related to a specific event and generate a storyline to help people understand the event evolution. First, a similarity calculation method is proposed to retrieve news articles related to the specific event, which combines textual similarity, temporal similarity and entity similarity. Then a multi-view attribute graph is constructed to represent the relationship between retrieved articles. Finally, a community detection algorithm is developed to segment and chain subevents in the graph. Experimental results on real-world datasets demonstrate that the proposed approach achieve better results than existing methods.0F0F.
CITATION STYLE
Huang, L., Lv, S., Zang, L., Su, Y., Han, J., & Hu, S. (2018). A Fresh Look at Understanding News Events Evolution. In The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018 (pp. 29–30). Association for Computing Machinery, Inc. https://doi.org/10.1145/3184558.3186913
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