Named entity recognition from scratch on social media

Date

2015-09-07

Author

Önal, Kezban Dilek
Karagöz, Pınar

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With the extensive amount of textual data flowing through social media platforms, the interest in Information Extraction (IE) on such textual data has increased. Named Entity Recognition (NER) is one of the basic problems of IE. State-of-the-art solutions for NER face an adaptation problem to informal texts from social media platforms. In this study, we addressed this generalization problem with the NLP from scratch idea that has been shown to be successful for several NLP tasks on formal text. Experimental results have shown that word embeddings can be successfully used for NER on informal text.

Subject Keywords

NER, Word embeding, NLP from scratch, Social media

URI

https://hdl.handle.net/11511/88175

Conference Name

International Workshop on Mining Ubiquitous and Social Environments (MUSE 2015) ECML-PKDD, MUSE Workshop, (07 Eylül 2015)

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

K. D. Önal and P. Karagöz, “Named entity recognition from scratch on social media,” presented at the International Workshop on Mining Ubiquitous and Social Environments (MUSE 2015) ECML-PKDD, MUSE Workshop, (07 Eylül 2015), Porto, Portugal, 2015, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/88175.