Serbest Metin Adresler Ïçin Otomatik Standardizasyon Sistemi

Salih Cebeci; Merve Ozyilmaz; Gokhan Ince

doi:10.1109/SIU.2019.8806349

Serbest Metin Adresler Ïçin Otomatik Standardizasyon Sistemi

Salih Cebeci
, Merve Ozyilmaz
, Gokhan Ince

Bilgisayar Mühendisliği Bölümü

Hepsiexpress

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

4 Atıf (Scopus)

Özet

In cases where addresses entry should be entered as free text, it is necessary for the delivery service quality to be improved by correcting the errors and deficiencies of the addresses and standardizing them to geographic coordinate information. In our study, it is aimed to develop a system using Support Vector Machines algorithm which is used on matching free text address data with standard address. The model trained with using classified data serves to express the similarity between a free text address and a standard address as a numerical value. It is confirmed that using the developed system, queries made with free text addresses over a database created from 250.000 addresses, the system has achieved a matching accuracy exceeding 81%.

Tercüme edilen katkı başlığı	Automatic standardization system for free text addresses
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	27th Signal Processing and Communications Applications Conference, SIU 2019
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9781728119045
DOI'lar	https://doi.org/10.1109/SIU.2019.8806349
Yayın durumu	Yayınlandı - Nis 2019
Etkinlik	27th Signal Processing and Communications Applications Conference, SIU 2019 - Sivas, Turkey Süre: 24 Nis 2019 → 26 Nis 2019

Yayın serisi

Adı	27th Signal Processing and Communications Applications Conference, SIU 2019

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	27th Signal Processing and Communications Applications Conference, SIU 2019
Ülke/Bölge	Turkey
Şehir	Sivas
Periyot	24/04/19 → 26/04/19

Bibliyografik not

Publisher Copyright:
© 2019 IEEE.

Keywords

Distance algorithm
Text matching

Belgeye Erişim

10.1109/SIU.2019.8806349

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Cebeci, S., Ozyilmaz, M., & Ince, G. (2019). Serbest Metin Adresler Ïçin Otomatik Standardizasyon Sistemi. In 27th Signal Processing and Communications Applications Conference, SIU 2019 Makale 8806349 (27th Signal Processing and Communications Applications Conference, SIU 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2019.8806349

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title = "Serbest Metin Adresler {\"I}{\c c}in Otomatik Standardizasyon Sistemi",

abstract = "In cases where addresses entry should be entered as free text, it is necessary for the delivery service quality to be improved by correcting the errors and deficiencies of the addresses and standardizing them to geographic coordinate information. In our study, it is aimed to develop a system using Support Vector Machines algorithm which is used on matching free text address data with standard address. The model trained with using classified data serves to express the similarity between a free text address and a standard address as a numerical value. It is confirmed that using the developed system, queries made with free text addresses over a database created from 250.000 addresses, the system has achieved a matching accuracy exceeding 81\%.",

keywords = "Distance algorithm, Text matching",

author = "Salih Cebeci and Merve Ozyilmaz and Gokhan Ince",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 27th Signal Processing and Communications Applications Conference, SIU 2019 ; Conference date: 24-04-2019 Through 26-04-2019",

year = "2019",

month = apr,

doi = "10.1109/SIU.2019.8806349",

language = "T{\"u}rk{\c c}e",

series = "27th Signal Processing and Communications Applications Conference, SIU 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "27th Signal Processing and Communications Applications Conference, SIU 2019",

address = "United States",

}

Cebeci, S, Ozyilmaz, M & Ince, G 2019, Serbest Metin Adresler Ïçin Otomatik Standardizasyon Sistemi. in 27th Signal Processing and Communications Applications Conference, SIU 2019., 8806349, 27th Signal Processing and Communications Applications Conference, SIU 2019, Institute of Electrical and Electronics Engineers Inc., 27th Signal Processing and Communications Applications Conference, SIU 2019, Sivas, Turkey, 24/04/19. https://doi.org/10.1109/SIU.2019.8806349

Serbest Metin Adresler Ïçin Otomatik Standardizasyon Sistemi. / Cebeci, Salih; Ozyilmaz, Merve; Ince, Gokhan.
27th Signal Processing and Communications Applications Conference, SIU 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8806349 (27th Signal Processing and Communications Applications Conference, SIU 2019).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Serbest Metin Adresler Ïçin Otomatik Standardizasyon Sistemi

AU - Cebeci, Salih

AU - Ozyilmaz, Merve

AU - Ince, Gokhan

PY - 2019/4

Y1 - 2019/4

N2 - In cases where addresses entry should be entered as free text, it is necessary for the delivery service quality to be improved by correcting the errors and deficiencies of the addresses and standardizing them to geographic coordinate information. In our study, it is aimed to develop a system using Support Vector Machines algorithm which is used on matching free text address data with standard address. The model trained with using classified data serves to express the similarity between a free text address and a standard address as a numerical value. It is confirmed that using the developed system, queries made with free text addresses over a database created from 250.000 addresses, the system has achieved a matching accuracy exceeding 81%.

AB - In cases where addresses entry should be entered as free text, it is necessary for the delivery service quality to be improved by correcting the errors and deficiencies of the addresses and standardizing them to geographic coordinate information. In our study, it is aimed to develop a system using Support Vector Machines algorithm which is used on matching free text address data with standard address. The model trained with using classified data serves to express the similarity between a free text address and a standard address as a numerical value. It is confirmed that using the developed system, queries made with free text addresses over a database created from 250.000 addresses, the system has achieved a matching accuracy exceeding 81%.

KW - Distance algorithm

KW - Text matching

UR - https://www.scopus.com/pages/publications/85071977449

U2 - 10.1109/SIU.2019.8806349

DO - 10.1109/SIU.2019.8806349

M3 - Konferans katkısı

AN - SCOPUS:85071977449

T3 - 27th Signal Processing and Communications Applications Conference, SIU 2019

BT - 27th Signal Processing and Communications Applications Conference, SIU 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 27th Signal Processing and Communications Applications Conference, SIU 2019

Y2 - 24 April 2019 through 26 April 2019

ER -

Serbest Metin Adresler Ïçin Otomatik Standardizasyon Sistemi

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

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