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

Translated title of the contribution: Automatic standardization system for free text addresses

Salih Cebeci, Merve Ozyilmaz, Gokhan Ince

Department of Computer Engineering

Hepsiexpress

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

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%.

Translated title of the contribution	Automatic standardization system for free text addresses
Original language	Turkish
Title of host publication	27th Signal Processing and Communications Applications Conference, SIU 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728119045
DOIs	https://doi.org/10.1109/SIU.2019.8806349
Publication status	Published - Apr 2019
Event	27th Signal Processing and Communications Applications Conference, SIU 2019 - Sivas, Turkey Duration: 24 Apr 2019 → 26 Apr 2019

Publication series

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

Conference

Conference	27th Signal Processing and Communications Applications Conference, SIU 2019
Country/Territory	Turkey
City	Sivas
Period	24/04/19 → 26/04/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

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10.1109/SIU.2019.8806349

Cite this

Cebeci, S., Ozyilmaz, M., & Ince, G. (2019). Serbest Metin Adresler Ïçin Otomatik Standardizasyon Sistemi. In 27th Signal Processing and Communications Applications Conference, SIU 2019 Article 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",

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doi = "10.1109/SIU.2019.8806349",

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

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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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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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

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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

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