ダウンロード数: 144
このアイテムのファイル:
| ファイル | 記述 | サイズ | フォーマット | |
|---|---|---|---|---|
| JCDL.2019.00108.pdf | 547.84 kB | Adobe PDF | 見る/開く |
完全メタデータレコード
| DCフィールド | 値 | 言語 |
|---|---|---|
| dc.contributor.author | Färber, Michael | en |
| dc.contributor.author | Nishioka, Chifumi | en |
| dc.contributor.author | Jatowt, Adam | en |
| dc.contributor.alternative | 西岡, 千文 | ja |
| dc.date.accessioned | 2019-12-03T05:15:32Z | - |
| dc.date.available | 2019-12-03T05:15:32Z | - |
| dc.date.issued | 2019 | - |
| dc.identifier.isbn | 9781728115474 | - |
| dc.identifier.uri | http://hdl.handle.net/2433/244872 | - |
| dc.description | 2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL): June 2 2019 to June 6 2019 Champaign, IL, USA. | en |
| dc.description.abstract | In this paper, we present a system for exploring the temporal trends of scientific concepts. Scientific concepts were captured by extracting noun phrases and entities from all computer science papers of arXiv.org. Our system allows users to review the time series of numerous concepts and to identify positively and negatively trending concepts. By applying clustering techniques and cluster analysis visualizations, it can also present concepts which share the same usage patterns over time. Our system can be beneficial for both ordinary researchers of any field and for researchers working in bibliometrics and scientometrics in order to investigate the evolution of scientific concepts. | en |
| dc.format.mimetype | application/pdf | - |
| dc.language.iso | eng | - |
| dc.publisher | IEEE | en |
| dc.rights | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en |
| dc.rights | The full-text file will be made open to the public on 1 June 2021 in accordance with publisher's 'Terms and Conditions for Self-Archiving'. | en |
| dc.rights | この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。 | ja |
| dc.rights | This is not the published version. Please cite only the published version. | en |
| dc.subject | trend detection | en |
| dc.subject | scholarly data | en |
| dc.subject | bibliometrics | en |
| dc.subject | time series | en |
| dc.title | ScholarSight: Visualizing Temporal Trends of Scientific Concepts | en |
| dc.type | conference paper | - |
| dc.type.niitype | Conference Paper | - |
| dc.identifier.jtitle | 2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL) | - |
| dc.identifier.volume | 2019 | - |
| dc.identifier.issue | 1 | - |
| dc.identifier.spage | 438 | - |
| dc.identifier.epage | 439 | - |
| dc.relation.doi | 10.1109/JCDL.2019.00108 | - |
| dc.textversion | author | - |
| dc.address | University of Freiburg | en |
| dc.address | Kyoto University | en |
| dc.address | Kyoto University | en |
| dcterms.accessRights | open access | - |
| datacite.date.available | 2021-06-01 | - |
| 出現コレクション: | 学術雑誌掲載論文等 | |
このリポジトリに保管されているアイテムはすべて著作権により保護されています。