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arXiv · 1812.03781

Inflo: News Categorization and Keyphrase Extraction for Implementation in an Aggregation System

Pranav A·Nick Sukiennik·Pan Hui
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Abstract

The work herein describes a system for automatic news category and keyphrase labeling, presented in the context of our motivation to improve the speed at which a user can find relevant and interesting content within an aggregation platform. A set of 12 discrete categories were applied to over 500,000 news articles for training a neural network, to be used to facilitate the more in-depth task of extracting the most significant keyphrases. The latter was done using three methods: statistical, graphical and numerical, using the pre-identified category label to improve relevance of extracted phrases. The results are presented in a demo in which the articles are pre-populated via News API, and upon being selected, the category and keyphrase labels will be computed via the methods explained herein.

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Pranav A, Nick Sukiennik, Pan Hui. 2018-12-10. Inflo: News Categorization and Keyphrase Extraction for Implementation in an Aggregation System. https://arxiv.org/abs/1812.03781

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