Name
Abstract | ||
|---|---|---|
The demand for a tool for summarizing emerging topics is increasing in modern life since the tool can deliver well-organized information to its users. Even though there are already a number of successful search systems, the system which automatically summarizes and organizes the content of emerging topics is still in its infancy. To fulfill such demand, we introduce an automated report generation system that generates a well-summarized human-readable report for emerging topics. In this report generation system, emerging topics are automatically discovered by a topic model and news articles are indexed by the discovered topics. Then, a topical summary and a timeline summary for each topic is generated by a topical multi-document summarizer and a timeline summarizer respectively. In order to enhance the apprehensibility of the users, the proposed report system provides two report modes. One is Today's Briefing which summarizes five discovered topics of every day, and the other is Full Report which shows a long-term view of each topic with a detailed topical summary and an important event timeline.
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Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3397271.3401409 | SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval
Virtual Event
China
July, 2020 |
DocType | ISBN | Citations |
Conference | 978-1-4503-8016-4 | 0 |
PageRank | References | Authors |
0.34 | 2 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yunseok Noh | 1 | 10 | 2.69 |
| Yongmin Shin | 2 | 0 | 0.34 |
| Junmo Park | 3 | 0 | 1.35 |
| A-Yeong Kim | 4 | 26 | 2.88 |
| Su-Jeong Choi | 5 | 0 | 1.01 |
| Hyun-Je Song | 6 | 33 | 9.58 |
| Seong-Bae Park | 7 | 311 | 47.31 |
| Seyoung Park | 8 | 76 | 14.48 |