A keyword recommendation method using CorKeD words and its application to earth science data

Youichi Ishida; Toshiyuki Shimizu; Masatoshi Yoshikawa

doi:10.1007/978-3-319-28940-3_8

A keyword recommendation method using CorKeD words and its application to earth science data

Youichi Ishida, Toshiyuki Shimizu, Masatoshi Yoshikawa

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

1 Citation (Scopus)

Abstract

In various research domains, data providers themselves annotate their own data with keywords from a controlled vocabulary. However, since selecting keywords requires extensive knowledge of the domain and the controlled vocabulary, even data providers have difficulty in selecting appropriate keywords from the vocabulary. Therefore, we propose a method for recommending relevant keywords in a controlled vocabulary to data providers. We focus on a keyword definition, and calculate the similarity between an abstract text of data and the keyword definition. Moreover, considering that there are unnecessary words in the calculation, we extract CorKeD (Corpus-based Keyword Decisive) words from a target domain corpus so that we can measure the similarity appropriately. We conduct an experiment on earth science data, and verify the effectiveness of extracting the CorKeD words, which are the terms that better characterize the domain.

Original language	English
Title of host publication	Information Retrieval Technology - 11th Asia Information Retrieval Societies Conference, AIRS 2015, Proceedings
Editors	Falk Scholer, Guido Zuccon, Shlomo Geva, Aixin Sun, Hideo Joho, Peng Zhang
Publisher	Springer Verlag
Pages	96-108
Number of pages	13
ISBN (Print)	9783319289397
DOIs	https://doi.org/10.1007/978-3-319-28940-3_8
Publication status	Published - 2015
Externally published	Yes
Event	11th Asia Information Retrieval Societies Conference, AIRS 2015 - Brisbane, Australia Duration: Dec 2 2015 → Dec 4 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9460
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th Asia Information Retrieval Societies Conference, AIRS 2015
Country/Territory	Australia
City	Brisbane
Period	12/2/15 → 12/4/15

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-28940-3_8

Cite this

Ishida, Y., Shimizu, T., & Yoshikawa, M. (2015). A keyword recommendation method using CorKeD words and its application to earth science data. In F. Scholer, G. Zuccon, S. Geva, A. Sun, H. Joho, & P. Zhang (Eds.), Information Retrieval Technology - 11th Asia Information Retrieval Societies Conference, AIRS 2015, Proceedings (pp. 96-108). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9460). Springer Verlag. https://doi.org/10.1007/978-3-319-28940-3_8

A keyword recommendation method using CorKeD words and its application to earth science data. / Ishida, Youichi; Shimizu, Toshiyuki; Yoshikawa, Masatoshi.
Information Retrieval Technology - 11th Asia Information Retrieval Societies Conference, AIRS 2015, Proceedings. ed. / Falk Scholer; Guido Zuccon; Shlomo Geva; Aixin Sun; Hideo Joho; Peng Zhang. Springer Verlag, 2015. p. 96-108 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9460).

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

Ishida, Y, Shimizu, T & Yoshikawa, M 2015, A keyword recommendation method using CorKeD words and its application to earth science data. in F Scholer, G Zuccon, S Geva, A Sun, H Joho & P Zhang (eds), Information Retrieval Technology - 11th Asia Information Retrieval Societies Conference, AIRS 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9460, Springer Verlag, pp. 96-108, 11th Asia Information Retrieval Societies Conference, AIRS 2015, Brisbane, Australia, 12/2/15. https://doi.org/10.1007/978-3-319-28940-3_8

Ishida Y, Shimizu T, Yoshikawa M. A keyword recommendation method using CorKeD words and its application to earth science data. In Scholer F, Zuccon G, Geva S, Sun A, Joho H, Zhang P, editors, Information Retrieval Technology - 11th Asia Information Retrieval Societies Conference, AIRS 2015, Proceedings. Springer Verlag. 2015. p. 96-108. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-28940-3_8

Ishida, Youichi ; Shimizu, Toshiyuki ; Yoshikawa, Masatoshi. / A keyword recommendation method using CorKeD words and its application to earth science data. Information Retrieval Technology - 11th Asia Information Retrieval Societies Conference, AIRS 2015, Proceedings. editor / Falk Scholer ; Guido Zuccon ; Shlomo Geva ; Aixin Sun ; Hideo Joho ; Peng Zhang. Springer Verlag, 2015. pp. 96-108 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "In various research domains, data providers themselves annotate their own data with keywords from a controlled vocabulary. However, since selecting keywords requires extensive knowledge of the domain and the controlled vocabulary, even data providers have difficulty in selecting appropriate keywords from the vocabulary. Therefore, we propose a method for recommending relevant keywords in a controlled vocabulary to data providers. We focus on a keyword definition, and calculate the similarity between an abstract text of data and the keyword definition. Moreover, considering that there are unnecessary words in the calculation, we extract CorKeD (Corpus-based Keyword Decisive) words from a target domain corpus so that we can measure the similarity appropriately. We conduct an experiment on earth science data, and verify the effectiveness of extracting the CorKeD words, which are the terms that better characterize the domain.",

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AU - Ishida, Youichi

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AB - In various research domains, data providers themselves annotate their own data with keywords from a controlled vocabulary. However, since selecting keywords requires extensive knowledge of the domain and the controlled vocabulary, even data providers have difficulty in selecting appropriate keywords from the vocabulary. Therefore, we propose a method for recommending relevant keywords in a controlled vocabulary to data providers. We focus on a keyword definition, and calculate the similarity between an abstract text of data and the keyword definition. Moreover, considering that there are unnecessary words in the calculation, we extract CorKeD (Corpus-based Keyword Decisive) words from a target domain corpus so that we can measure the similarity appropriately. We conduct an experiment on earth science data, and verify the effectiveness of extracting the CorKeD words, which are the terms that better characterize the domain.

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A keyword recommendation method using CorKeD words and its application to earth science data

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