Novel Keyword Extraction and Language Detection Approaches

• URL: http://arxiv.org/abs/2009.11832v1
• Date: Thu, 24 Sep 2020 17:28:59 GMT
• Title: Novel Keyword Extraction and Language Detection Approaches
• Authors: Malgorzata Pikies, Andronicus Riyono, Junade Ali
• Abstract summary: We propose a fast novel approach to string tokenisation for fuzzy language matching. We experimentally demonstrate an 83.6% decrease in processing time. We find the Accept-Language header is 14% more likely to match the classification than the IP Address.
• Score: 0.6445605125467573
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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