研究生: |
王涵 Wang, Han |
---|---|
論文名稱: |
Timeline Summarization for Event-related Facts and Public Issues on Chinese Social Media Platform Timeline Summarization for Event-related Facts and Public Issues on Chinese Social Media Platform |
指導教授: |
柯佳伶
Koh, Jia-Ling |
學位類別: |
碩士 Master |
系所名稱: |
資訊工程學系 Department of Computer Science and Information Engineering |
論文出版年: | 2017 |
畢業學年度: | 105 |
語文別: | 英文 |
論文頁數: | 62 |
中文關鍵詞: | Timeline summarization 、Sub-event detection 、Text data mining |
英文關鍵詞: | Timeline summarization, Sub-event detection, Text data mining |
DOI URL: | https://doi.org/10.6345/NTNU202203015 |
論文種類: | 學術論文 |
相關次數: | 點閱:106 下載:11 |
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無中文摘要
In this paper, we proposed an approach to automatically generate timeline summarization for sub-event discussions related to a query event without supervised learning. In order to select event-related sentences, we designed a two-stage method to extract representative entity terms in the event-related discussions and filter out most of the sentences semantically un-related to the query event. A rule-based method was applied to extract sentences which describing sub-events. After that, the discussions are assigned to the corresponding sub-events according to the semantic relatedness measure. Finally, according to the occurring time of each sub-event, the timeline summarization is organized.
We evaluated the performance of the proposed method on the real-world datasets. The experiment results showed that each processing step perform effectively. Especially, most noise sentences could be filtered by the proposed method. Moreover, the final timeline summarization graded by users is proven to be useful to well understand the discussion trend of a sub-event
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