Comparing the Performance of Different NLP Toolkits in Formal and Social Media Text



Natural Language Processing


5th Symposium on Languages, Applications and Technologies (SLATE'16), June 2016


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Year 2019 : 5 citations

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Year 2018 : 6 citations

 Silva, N. G. N. (2018). Information extraction from unstructured recipe data. Master’s thesis, Universidade do Porto.

 Fragkou, P. (2018). Combining information extraction and text segmentation methods in greek texts. Artificial Intelligence Research, 7(1).

 Neumer, T. (2018). Efficient natural language processing for automated recruiting on the example of a software engineering talent-pool. Master’s thesis, Technische Universitat Munchen.

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Year 2017 : 4 citations

 Baumer, F. S. (2017). Indikatorbasierte Erkennung und Kompensation von ungenauen und unvollstandig beschriebenen Softwareanforderungen. PhD thesis, Universitat Paderborn.

 da Gama Batista, F. D. (2017). Using named entity recognition for relevance detection in social network messages. Master’s thesis, Universidade do Porto.

 Fragkou, P. (2017). Applying named entity recognition and co-reference resolution for seg- menting english texts. Progress in Artificial Intelligence. (online on May 2017)

 Batista,F. and Figueira, A. (2017).The complementary nature of different NLP toolkits for named entity recognition in social media. In Progress in Artificial Intelligence - Proceedings of 18th Portuguese Conference on Artificial Intelligence, Porto, Portugal, September 5-8, 2017, volume 10423 of LNCS, pages 803–814. Springer.