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Novel Keyword Extraction and Language Detection Approaches

2020-09-24 17:28:59
Malgorzata Pikies, Andronicus Riyono, Junade Ali
arXiv_CL
           
Abstract

Fuzzy string matching and language classification are important tools in Natural Language Processing pipelines, this paper provides advances in both areas. We propose a fast novel approach to string tokenisation for fuzzy language matching and experimentally demonstrate an 83.6% decrease in processing time with an estimated improvement in recall of 3.1% at the cost of a 2.6% decrease in precision. This approach is able to work even where keywords are subdivided into multiple words, without needing to scan character-to-character. So far there has been little work considering using metadata to enhance language classification algorithms. We provide observational data and find the Accept-Language header is 14% more likely to match the classification than the IP Address.

Abstract (translated)

URL

https://arxiv.org/abs/2009.11832

PDF

https://arxiv.org/pdf/2009.11832.pdf

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