E3 : Keyphrase based News Event Exploration Engine
Nikita Jain, Swati Gupta, Dhaval Patel
TL;DR
E3 is a system that extracts and enriches keyphrases from news content to provide users with a comprehensive overview of news events, highlighting the most novel and active keyphrases based on publication data.
Contribution
The paper introduces E3, a novel keyphrase extraction and enrichment system that emphasizes identifying the most interesting news keyphrases using novelty and activeness metrics.
Findings
E3 effectively extracts relevant keyphrases from news articles.
E3 ranks and tags keyphrases to enhance informational value.
E3 identifies the most active and novel keyphrases based on publication dates.
Abstract
This paper presents a novel system E3 for extracting keyphrases from news content for the purpose of offering the news audience a broad overview of news events, with especially high content volume. Given an input query, E3 extracts keyphrases and enrich them by tagging, ranking and finding role for frequently associated keyphrases. Also, E3 finds the novelty and activeness of keyphrases using news publication date, to identify the most interesting and informative keyphrases.
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