KIISE Transactions on Computing Practices (정보과학회 컴퓨팅의 실제 논문지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Accuracy Improvement Methods for String Similarity Measurement in POI(Point Of Interest) Data Retrieval

POI(Point Of Interest) 데이터 검색에서 문자열 유사도 측정 정확도 향상 기법

  • 고은별 (숙명여자대학교 멀티미디어과학과) ;
  • 이종우 (숙명여자대학교 멀티미디어과학과)
  • Received : 2014.05.07
  • Accepted : 2014.06.20
  • Published : 2014.09.15
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Abstract

With the development of smart transportation, people are likely to find their paths by using navigation and map application. However, the existing retrieval system cannot output the correct retrieval result due to the inaccurate query. In order to remedy this problem, set-based POI search algorithm was proposed. Subsequently, additionally a method for measuring POI name similarity and POI search algorithm supporting classifying duplicate characters were proposed. These algorithms tried to compensate the insufficient part of the compensate set-based POI search algorithm. In this paper, accuracy improvement methods for measuring string similarity in POI data retrieval system are proposed. By formulization, similarity measurement scheme is systematized and generalized with the development of transportation. As a result, it improves the accuracy of the retrieval result. From the experimental results, we can observe that our accuracy improvement methods show better performance than the previous algorithms.

교통의 발달로 활동범위가 넓은 현대인들은 네비게이션과 지도 앱을 통한 길찾기 검색을 자주 이용한다. 하지만 기존 검색 시스템에서는 부정확한 질의어가 입력되면 원하는 결과를 출력하지 못한다. 이 문제를 해결하기 위해 집합-기반 POI 검색 알고리즘이 등장했고 이어 문자열 유사도 측정 기법, 중복 글자를 고려한 검색 알고리즘이 연구되었다. 본 논문에서는 이전에 연구된 문자열 유사도 측정 알고리즘의 정확도를 향상시킨 기법을 제안한다. 기존 문자열 유사도 측정 기법에서 고려하지 않았던 고유어의 추정단계와 중복 단어를 고려한 블록 및 블록 나열 순서 구하기를 추가하고 측정 기법을 수식화한다. 이를 통해 측정방법을 체계적으로 표현하고 일반화함으로써 POI 검색 결과의 정확도를 향상시킨다. 실험을 통해 본 논문에서 제시하는 기법이 검색 결과 및 검색 순위의 정확도를 향상시킨다는 것을 확인하였다.

Keywords

Acknowledgement

Supported by : 한국연구재단

References

  1. Seung Weon Yang, Hyun Young Lee, Ji Hyun Wang, "A Point-Of-Interest Allomorph Database Construction System," Journal of KIISE: Software and Application, Vol. 36, No. 3, pp. 226-235, 2009. (in Korean)
  2. Steven C.H. Hoi, Jiebo Luo, Susanne Boll, Dong Xu, and Rong Jin, Social Media Modeling and Computing, p. 245, Springer, 2011.
  3. Xinyan Zhu and Chunhui Zhou, "POI Inquiries and data update based on LBS," Proc. of the International Symposium on Information Engineering and Electronic Commerce(IEEC), pp. 730-734, 2009.
  4. EunBi Go, JaeWon Lee, JongWoo Lee, An Efficient Set-based POI Search Algorithm [Online]. Available : http://mm.sookmyung.ac.kr/-zinc/SetPOISearch.pdf
  5. AhYeon Jin, JaeWon Lee, Jongwoo Lee, "Measuring Method of String Similarity for POI Data Retrieval," Journal of KIISE : Computing Practices and Letters, Vol. 19, No. 4, pp. 177-185, 2013.
  6. EunByul Ko, JongWoo Lee, "Implementation of A Set-based POI Search Algorithm Supporting Classifying Duplicate Characters," Journal of Digital Contents Society, Vol. 14, No. 4, pp. 465-471, 2013. https://doi.org/10.9728/dcs.2013.14.4.463
  7. Yuen- Hsien Tsieng, Da-Wei Juang and Shiu-Han Chen, "Global and Local Term Expansion for Text Retrieval," Proc. of the Fourth NTCIR Workshop on Evaluation of Information Retrieval, 2004.
  8. Soonjin Kwon, Chuleui Hong, Wonil Kim, "Revealing Hidden Relations between Query-Words for an Efficient Inducing User's Intention of an Information Search," Journal of the Institute of Electronics Engineers of Korea, Vol. 49, No. 2, pp. 44-52, 2012.
  9. Ian Ruthven and Mounia Lalmas, "A survey on the use of relevance feedback for information access systems," Knowledge Engineering Review, Vol. 18, No. 2, pp. 95-145, 2003. https://doi.org/10.1017/S0269888903000638
  10. EunByul Ko, JongWoo Lee, "Design of A Set-based POI Search Algorithm Supporting Classifying Duplicate Characters," Proceedings of the Korea Multimedia Society Conference, Vol. 16, No. 2, pp. 244-246, 2013.