Evaluation Index to Find Relevant Papers

Improvement of Focused Citation Count

Tetsuya Nakatoh, Sachio Hirokawa

研究成果: 著書/レポートタイプへの貢献会議での発言

抄録

During a research survey, it is very important to quickly find suitable papers. It is common practice for researchers to select relevant papers by searching using query keywords, ranking those papers by citation number, and checking in order from the highest ranked papers. However, if a paper that had a query keyword as a non-primary word had many citations, it would hinder any attempt to quickly find the appropriate paper. We have already proposed a Focused Citation Count (FCC) that supports the finding of suitable papers by setting the number of citations as a more appropriate evaluation index by properly focusing on cited papers which are the sources of citation counts. In this study, we propose an improved method of FCC. Since FCC is easily affected by the size of the cited number, this proposal aims to reduce its characteristics. We evaluate the proposed method using actual paper data and try to confirm its effectiveness.

元の言語英語
ホスト出版物のタイトルHuman Interface and the Management of Information. Visual Information and Knowledge Management - Thematic Area, HIMI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings
編集者Sakae Yamamoto, Hirohiko Mori
出版者Springer Verlag
ページ555-566
ページ数12
ISBN(印刷物)9783030226596
DOI
出版物ステータス出版済み - 1 1 2019
イベントThematic Area on Human Interface and the Management of Information, HIMI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019 - Orlando, 米国
継続期間: 7 26 20197 31 2019

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11569 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

会議

会議Thematic Area on Human Interface and the Management of Information, HIMI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019
米国
Orlando
期間7/26/197/31/19

Fingerprint

Citations
Count
Evaluation
Query
Ranking
Evaluate

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

これを引用

Nakatoh, T., & Hirokawa, S. (2019). Evaluation Index to Find Relevant Papers: Improvement of Focused Citation Count. : S. Yamamoto, & H. Mori (版), Human Interface and the Management of Information. Visual Information and Knowledge Management - Thematic Area, HIMI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings (pp. 555-566). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 11569 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-22660-2_41

Evaluation Index to Find Relevant Papers : Improvement of Focused Citation Count. / Nakatoh, Tetsuya; Hirokawa, Sachio.

Human Interface and the Management of Information. Visual Information and Knowledge Management - Thematic Area, HIMI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings. 版 / Sakae Yamamoto; Hirohiko Mori. Springer Verlag, 2019. p. 555-566 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻 11569 LNCS).

研究成果: 著書/レポートタイプへの貢献会議での発言

Nakatoh, T & Hirokawa, S 2019, Evaluation Index to Find Relevant Papers: Improvement of Focused Citation Count. : S Yamamoto & H Mori (版), Human Interface and the Management of Information. Visual Information and Knowledge Management - Thematic Area, HIMI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 巻. 11569 LNCS, Springer Verlag, pp. 555-566, Thematic Area on Human Interface and the Management of Information, HIMI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019, Orlando, 米国, 7/26/19. https://doi.org/10.1007/978-3-030-22660-2_41
Nakatoh T, Hirokawa S. Evaluation Index to Find Relevant Papers: Improvement of Focused Citation Count. : Yamamoto S, Mori H, 編集者, Human Interface and the Management of Information. Visual Information and Knowledge Management - Thematic Area, HIMI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings. Springer Verlag. 2019. p. 555-566. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-22660-2_41
Nakatoh, Tetsuya ; Hirokawa, Sachio. / Evaluation Index to Find Relevant Papers : Improvement of Focused Citation Count. Human Interface and the Management of Information. Visual Information and Knowledge Management - Thematic Area, HIMI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings. 編集者 / Sakae Yamamoto ; Hirohiko Mori. Springer Verlag, 2019. pp. 555-566 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{642c04aec96c4e2db81fce613987b5cc,
title = "Evaluation Index to Find Relevant Papers: Improvement of Focused Citation Count",
abstract = "During a research survey, it is very important to quickly find suitable papers. It is common practice for researchers to select relevant papers by searching using query keywords, ranking those papers by citation number, and checking in order from the highest ranked papers. However, if a paper that had a query keyword as a non-primary word had many citations, it would hinder any attempt to quickly find the appropriate paper. We have already proposed a Focused Citation Count (FCC) that supports the finding of suitable papers by setting the number of citations as a more appropriate evaluation index by properly focusing on cited papers which are the sources of citation counts. In this study, we propose an improved method of FCC. Since FCC is easily affected by the size of the cited number, this proposal aims to reduce its characteristics. We evaluate the proposed method using actual paper data and try to confirm its effectiveness.",
author = "Tetsuya Nakatoh and Sachio Hirokawa",
year = "2019",
month = "1",
day = "1",
doi = "10.1007/978-3-030-22660-2_41",
language = "English",
isbn = "9783030226596",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "555--566",
editor = "Sakae Yamamoto and Hirohiko Mori",
booktitle = "Human Interface and the Management of Information. Visual Information and Knowledge Management - Thematic Area, HIMI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings",
address = "Germany",

}

TY - GEN

T1 - Evaluation Index to Find Relevant Papers

T2 - Improvement of Focused Citation Count

AU - Nakatoh, Tetsuya

AU - Hirokawa, Sachio

PY - 2019/1/1

Y1 - 2019/1/1

N2 - During a research survey, it is very important to quickly find suitable papers. It is common practice for researchers to select relevant papers by searching using query keywords, ranking those papers by citation number, and checking in order from the highest ranked papers. However, if a paper that had a query keyword as a non-primary word had many citations, it would hinder any attempt to quickly find the appropriate paper. We have already proposed a Focused Citation Count (FCC) that supports the finding of suitable papers by setting the number of citations as a more appropriate evaluation index by properly focusing on cited papers which are the sources of citation counts. In this study, we propose an improved method of FCC. Since FCC is easily affected by the size of the cited number, this proposal aims to reduce its characteristics. We evaluate the proposed method using actual paper data and try to confirm its effectiveness.

AB - During a research survey, it is very important to quickly find suitable papers. It is common practice for researchers to select relevant papers by searching using query keywords, ranking those papers by citation number, and checking in order from the highest ranked papers. However, if a paper that had a query keyword as a non-primary word had many citations, it would hinder any attempt to quickly find the appropriate paper. We have already proposed a Focused Citation Count (FCC) that supports the finding of suitable papers by setting the number of citations as a more appropriate evaluation index by properly focusing on cited papers which are the sources of citation counts. In this study, we propose an improved method of FCC. Since FCC is easily affected by the size of the cited number, this proposal aims to reduce its characteristics. We evaluate the proposed method using actual paper data and try to confirm its effectiveness.

UR - http://www.scopus.com/inward/record.url?scp=85069883525&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85069883525&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-22660-2_41

DO - 10.1007/978-3-030-22660-2_41

M3 - Conference contribution

SN - 9783030226596

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 555

EP - 566

BT - Human Interface and the Management of Information. Visual Information and Knowledge Management - Thematic Area, HIMI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings

A2 - Yamamoto, Sakae

A2 - Mori, Hirohiko

PB - Springer Verlag

ER -