Earticle

초록

영어

Microblog has been a dominant social-network platform. Many social events spread fast on microblogging platforms, because of the high interactivity and large amounts of users of microblogging platforms. However, users can only search for interested events on microblogging platforms by keywords, yielding high redundancy of search results as well as the lack of complete description on events (owing to the limitation on the length of microblogs). Aiming to solve these problems, we propose a new approach to automatically generate event abstracts for microblog events. We summarize an event via two aspects, namely an event-description set and a user-opinion set. For extracting the event description for an event, we first partition microblogs into a set of short sentences. These sentences are further ranked by computing the relevance to the event based on a graph model and the most relevant sentences are selected as the set of event description. For extracting user opinions on an event, we propose a supervised learning model that is based on the set of long sentences extracted from microblogs. We conduct experiments on a data set consisting of 14 events crawled from the Sina Weibo. The experiment results suggest the effectiveness of the proposed approach.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Framework of Event Detection and Summarization
  3.1. System Architecture
  3.2. Textual Pre-processing
  3.3. Sentence Importance Judging
  3.4. TF-IDF
 4. Sentences Selection
  4.1. Event Related Sentences Selection
  4.2. General Sentences Selection
 5. Performance Evaluation
  5.1. Dataset
  5.2. Event Summary Generation
  5.3. General Sentence Extraction
 6. Conclusion
 Acknowledgments
 References

키워드

저자

• Jie Zhao [ School of Business, Anhui University ]
• Shuhan Liu [ School of Business, Anhui University ]
• Tong Cui [ School of Computer Science and Technology, University of Science and Technology of China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605