Journal article
Discovering Event Evolution Graphs From News Corpora
IEEE transactions on systems, man and cybernetics. Part A, Systems and humans, v 39(4), pp 850-863
Jul 2009
Abstract
Given the advance of Internet technologies, we can now easily extract hundreds or thousands of news stories of any ongoing incidents from newswires such as CNN.com, but the volume of information is too large for us to capture the blueprint. Information retrieval techniques such as topic detection and tracking are able to organize news stories as events, in a flat hierarchical structure, within a topic. However, they are incapable of presenting the complex evolution relationships between the events. We are interested to learn not only what the major events are but also how they develop within the topic. It is beneficial to identify the seminal events, the intermediary and ending events, and the evolution of these events. In this paper, we propose to utilize the event timestamp, event content similarity, temporal proximity, and document distributional proximity to model the event evolution relationships between events in an incident. An event evolution graph is constructed to present the underlying structure of events for efficient browsing and extracting of information. Case study and experiments are presented to illustrate and show the performance of our proposed technique. It is found that our proposed technique outperforms the baseline technique and other comparable techniques in previous work.
Metrics
Details
- Title
- Discovering Event Evolution Graphs From News Corpora
- Creators
- C.C Yang - Coll. of Inf. Sci. & Technol., Drexel Univ., Philadelphia, PAXiaodong Xiaodong ShiChih-Ping Chih-Ping Wei
- Publication Details
- IEEE transactions on systems, man and cybernetics. Part A, Systems and humans, v 39(4), pp 850-863
- Publisher
- IEEE
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000267434100013
- Scopus ID
- 2-s2.0-67650652459
- Other Identifier
- 991014877987704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Cybernetics
- Computer Science, Theory & Methods