Aggregating News Articles – NewsInn Algorithm

  • Radu Nicoara NewsInn, Bucharest, Romania
Keywords: News Aggregation, Text Classification, Natural Language Processing, Artificial Intelligence.

Abstract

NewsInn is an algorithm designed to aggregate articles from multiple news sources into one general, story-based meta-article. This entity is then displayed by calculating the most relevant news article in relation to it, and by listing underneath it the remainder of articles. Using a simple User Interface, the algorithm makes it easy for end users to understand current events, the coverage that they have and the impact that the story carries.

Using multiple Natural Language Processing techniques, Newsinn manages to parse 19 different news source and aggregate more than 700 articles daily into their respective meta-articles. Seeing how even a human would have issues deciding if certain articles are related or not, as it depends on what criteria is used for making this decision, NewsInn uses different parameters to control the level of aggregation. 

References

– Algoritmi de Agregare si Procesare a Stirilor – Radu Nicoara (2016)

– NewsInn official Website

– Esuli, Andrea, and Fabrizio Sebastiani. "Sentiwordnet: A publicly available lexical resource for opinion mining." Proceedings of LREC. Vol. 6. 2006.

– Baldridge, Jason. "The opennlp project." URL: http://opennlp.apache.org/index.html, (accessed 2 February 2012) (2005).

– Mani, Inderjeet. Automatic summarization. Vol. 3. John Benjamins Publishing, 2001.

Published
2016-08-12
How to Cite
Nicoara, R. (2016). Aggregating News Articles – NewsInn Algorithm. International Journal of Computer (IJC), 22(1), 37-42. Retrieved from https://ijcjournal.org/index.php/InternationalJournalOfComputer/article/view/685
Section
Articles