On the bursty evolution of blogspace
WWW '03 Proceedings of the 12th international conference on World Wide Web
Query based event extraction along a timeline
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Discovering evolutionary theme patterns from text: an exploration of temporal text mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Formal models for expert finding in enterprise corpora
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Multidocument Summary Generation: Using Informative and Event Words
ACM Transactions on Asian Language Information Processing (TALIP)
FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04
Emotion Classification of Online News Articles from the Reader's Perspective
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Integrating multiple windows and document features for expert finding
Journal of the American Society for Information Science and Technology
Discovering the staring people from social networks
Proceedings of the 18th international conference on World wide web
Searching for events in the blogosphere
Proceedings of the 18th international conference on World wide web
| Hi-index | 0.00 |
Internet has become a resourceful platform for people to collect information. Specially, it becomes one of the main ways to understand a celebrity. However, the huge volume of information makes troubles for people to get what they really want. How to filter out needless information through numerous data and form a brief review of a celebrity become necessary for people to understand the person. In this paper, we propose a novel solution for understanding a celebrity by summarizing his most salient historical events, and a framework is outlined. The framework contains three main components: attention tracking, event mining from News, and event summarization. First, with the comparison of users' attention and media attention on a celebrity, News corpus is proved to be able to represent the users' attention. Second, keywords are extracted from the News according to different time periods for choosing summary sentences. Third, a final event description of the celebrity will be given. Finally, we will show the user interface of our system. Our experimental results show that the proposed solution can effectively process the news corpus and provide us with accurate description of the celebrity.