Cateye: A Hint-Enabled Search Engine Framework for Biomedical Classification Systems

Chia Jung Yang, Jung-Hsien Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Objective: We propose Cateye, a Python-based search engine framework tailored for searching in biomedical classification systems such as ICD-10, DSM-5, MeSH, and SNOMED CT. Many of the biomedical classification systems have coarse-grained and fine-grained structures to handle the different levels of information. The general-purpose search engines, which designed for document retrieval, face three major problems: Too strict terminology, not efficient search, and uncertainty to stop searching. These disadvantages make it painful to search in the classification systems. Materials and Methods: We used the ICD-10 coding systems as our sample materials. We design a hint bar which shown along with the search results and dramatically helps the users to formulate the correct query. A hint is a suggestion of search term which can best divide the search space into half-and-half. Results: The case studies show that our hint mechanism performs at least one step deeper per search step in most cases. Conclusion: The source code of Cateye for searching the classification systems associated with coarse-grained and fine-grained architecture is available at https://github.com/jeroyang/cateye.

Original languageEnglish
Title of host publicationNew Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers
EditorsChuan-Yu Chang, Chien-Chou Lin, Horng-Horng Lin
PublisherSpringer Verlag
Pages758-763
Number of pages6
ISBN (Print)9789811391897
DOIs
Publication statusPublished - 2019 Jan 1
Event23rd International Computer Symposium, ICS 2018 - Yunlin, Taiwan
Duration: 2018 Dec 202018 Dec 22

Publication series

NameCommunications in Computer and Information Science
Volume1013
ISSN (Print)1865-0929

Conference

Conference23rd International Computer Symposium, ICS 2018
CountryTaiwan
CityYunlin
Period18-12-2018-12-22

Fingerprint

Search engines
Search Engine
Computer systems
Terminology
Document Retrieval
Python
Fine Structure
Search Space
Divides
Coding
Framework
Mesh
Face
Query
Uncertainty
Term

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

Cite this

Yang, C. J., & Chiang, J-H. (2019). Cateye: A Hint-Enabled Search Engine Framework for Biomedical Classification Systems. In C-Y. Chang, C-C. Lin, & H-H. Lin (Eds.), New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers (pp. 758-763). (Communications in Computer and Information Science; Vol. 1013). Springer Verlag. https://doi.org/10.1007/978-981-13-9190-3_82
Yang, Chia Jung ; Chiang, Jung-Hsien. / Cateye : A Hint-Enabled Search Engine Framework for Biomedical Classification Systems. New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers. editor / Chuan-Yu Chang ; Chien-Chou Lin ; Horng-Horng Lin. Springer Verlag, 2019. pp. 758-763 (Communications in Computer and Information Science).
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abstract = "Objective: We propose Cateye, a Python-based search engine framework tailored for searching in biomedical classification systems such as ICD-10, DSM-5, MeSH, and SNOMED CT. Many of the biomedical classification systems have coarse-grained and fine-grained structures to handle the different levels of information. The general-purpose search engines, which designed for document retrieval, face three major problems: Too strict terminology, not efficient search, and uncertainty to stop searching. These disadvantages make it painful to search in the classification systems. Materials and Methods: We used the ICD-10 coding systems as our sample materials. We design a hint bar which shown along with the search results and dramatically helps the users to formulate the correct query. A hint is a suggestion of search term which can best divide the search space into half-and-half. Results: The case studies show that our hint mechanism performs at least one step deeper per search step in most cases. Conclusion: The source code of Cateye for searching the classification systems associated with coarse-grained and fine-grained architecture is available at https://github.com/jeroyang/cateye.",
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Yang, CJ & Chiang, J-H 2019, Cateye: A Hint-Enabled Search Engine Framework for Biomedical Classification Systems. in C-Y Chang, C-C Lin & H-H Lin (eds), New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers. Communications in Computer and Information Science, vol. 1013, Springer Verlag, pp. 758-763, 23rd International Computer Symposium, ICS 2018, Yunlin, Taiwan, 18-12-20. https://doi.org/10.1007/978-981-13-9190-3_82

Cateye : A Hint-Enabled Search Engine Framework for Biomedical Classification Systems. / Yang, Chia Jung; Chiang, Jung-Hsien.

New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers. ed. / Chuan-Yu Chang; Chien-Chou Lin; Horng-Horng Lin. Springer Verlag, 2019. p. 758-763 (Communications in Computer and Information Science; Vol. 1013).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Yang CJ, Chiang J-H. Cateye: A Hint-Enabled Search Engine Framework for Biomedical Classification Systems. In Chang C-Y, Lin C-C, Lin H-H, editors, New Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers. Springer Verlag. 2019. p. 758-763. (Communications in Computer and Information Science). https://doi.org/10.1007/978-981-13-9190-3_82