A Framework: Event Extraction from the Temporal Web

Abstract

Temporal-based mining is an attractive direction which is newly generated from the Data Mining field. By taking the time factor into account, some knowledge and interesting information, such as burst events and topic durations, can be mined out from data collections which are coordinated according to their duration (timestamp). Given the huge web as a temporal data collection, in this paper, we introduce a framework based on our current work. The main task is to find the association between two topics in different time slots (durations). Given a keyword as the main topic, we expect to find three kinds of topics which are relevant to the main topic: periodical topic, non-periodical topic and burst topic. These three types of topics can satisfy the needs of users with different requirements.