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Eventera: Real-Time Event Recommendation System from Massive Heterogeneous Online Media
Given massive heterogeneous online media, how can we summarize events, and discover causal relationships among them, in real time? Indeed we are living in a deluge of information, everyday hundreds of thousands of news articles are published, millions of postings from social media and internet forum...
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Main Authors: | , , , , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | Given massive heterogeneous online media, how can we summarize events, and discover causal relationships among them, in real time? Indeed we are living in a deluge of information, everyday hundreds of thousands of news articles are published, millions of postings from social media and internet forums are written, and billions of search queries are generated by Internet users. To convey user-interested news events and their big pictures for better understanding, building real-time event recommendation system is indispensable. Our proposed system, Eventera, aggregates massive online media from heterogeneous channels, summarizes them into events, discovers meaningful associations by bridging the events, and generates a sequence map of events that provides a big picture of how real life events interact with each other over time. We demonstrate how our system help users understand events and their causal relationships effectively. |
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ISSN: | 2375-9232 2375-9259 |
DOI: | 10.1109/ICDMW.2014.32 |