Summarizing Complex Events: a Cross-Modal Solution of Storylines Extraction and Reconstruction
Shize Xu, Shanshan Wang, Yan Zhang · 2013
The rapid development of Web2.0 leads to significant information redundancy.Especially for a complex news event, it is difficult to understand its general idea within a single coherent picture.A complex event often contains branches, intertwining narratives and side news which are all called storylines.In this paper, we propose a novel solution to tackle the challenging problem of storylines extraction and reconstruction.Specifically, we first investigate two requisite properties of an ideal storyline.Then a unified algorithm is devised to extract all effective storylines by optimizing these properties at the same time.Finally, we reconstruct all extracted lines and generate the high-quality story map.Experiments on real-world datasets show that our method is quite efficient and highly competitive, which can bring about quicker, clearer and deeper comprehension to readers.