Pregled bibliografske jedinice broj: 996758
Application of Distance Measurement NLP Methods for Address and Location Matching in Logistics
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.)., 2019. str. 137-150 doi:10.1007/978-3-030-14132-5_11
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Naslov
Application of Distance Measurement NLP Methods for Address and Location Matching in Logistics
Autori
Mršić, Leo
Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni
Knjiga
Studies in Computational Intelligence book series (SCI, volume 830)
Urednik/ci
Huk M., Maleszka M., Szczerbicki E.
Izdavač
Springer
Godina
2019
Raspon stranica
137-150
ISBN
978-3-030-14131-8
ISSN
1860-949X
Ključne riječi
Distance measurement NLP methods ; Address matching in logistics ; Location matching in logistics ; Text mining
Sažetak
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).
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti
