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Application of Distance Measurement NLP Methods for Address and Location Matching in Logistics (CROSBI ID 63787)

Prilog u knjizi | izvorni znanstveni rad | međunarodna recenzija

Mršić, Leo Application of Distance Measurement NLP Methods for Address and Location Matching in Logistics // Studies in Computational Intelligence book series (SCI, volume 830) / Huk M., Maleszka M., Szczerbicki E. (ur.).: Springer, 2019. str. 137-150 doi: 10.1007/978-3-030-14132-5_11

Podaci o odgovornosti

Mršić, Leo

engleski

Application of Distance Measurement NLP Methods for Address and Location Matching in Logistics

Paper is based on research based on linguistic terms denoting an address used for delivery services in logistic. Distance measurement NLP methods are widely usable in text mining and can be used to find the similarity among sentence or document. As part of logistics process, being able to determine correct address using machine learning we need to tackle issue of two addresses comparison (street name, city name etc.) is crucial for efficient service. This paper explains comparison techniques based on similarity score that can be calculated using distance measurement. As part of process, several distance measurements were compared while conclusion include results and recommendation on usage in address and location matching in logistics (post services).

Distance measurement NLP methods ; Address matching in logistics ; Location matching in logistics ; Text mining

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Podaci o prilogu

137-150.

objavljeno

10.1007/978-3-030-14132-5_11

Podaci o knjizi

Studies in Computational Intelligence book series (SCI, volume 830)

Huk M., Maleszka M., Szczerbicki E.

Springer

2019.

978-3-030-14131-8

1860-949X

Povezanost rada

Računarstvo, Informacijske i komunikacijske znanosti

Poveznice