Design and Implementation of Event Information Summarization System

In this research, we have designed and implemented an Event Information Summarization System (EISS) for collecting Event Info as a web-service. EISS collects mass event data from several non-uniform event website APIs and data sources. The Collected event data is visualized by some user-friendly user interfaces for consumer. EISS can summarize the event data in locational info and temporal info automatically and visualizes them to consumer on online maps. The Event Info is not showed to the consumer by a single list any longer. The consumer will experience the Event Info that is shown by locational online maps. Consumers also can set the query conditions or categories of events to filter out the events info that they need. We also designed and implemented a machine-learning algorithm to estimate the categories of event. EISS results in F1-Score to 0.47 by simple feature. We mentioned that some features are strong and positive correlate with categories expressly.