Management of scientific documents and visualization of citation relationships using weighted key scientific terms

Hui Wei; Youbing Zhao; Enjie Liu; Shaopeng Wu; Zhikun Deng; Farzad Parvinzamir; Feng Dong; Gordon Clapworthy

doi:10.5220/0005981501350143

Management of scientific documents and visualization of citation relationships using weighted key scientific terms

Hui Wei
, Youbing Zhao
, Enjie Liu
, Shaopeng Wu
, Zhikun Deng
, Farzad Parvinzamir
, Feng Dong
, Gordon Clapworthy

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

4 Citations (Scopus)

2 Downloads (Pure)

Abstract

Effective management and visualization of scientific and research documents can greatly assist researchers by improving understanding of relationships (e.g. citations) between the documents. This paper presents work on the management and visualization of large corpuses of scientific papers in order to help researchers explore their citation relationships. Term selection and weighting are used for mining citation relationships by identifying the most relevant. To this end, we present a variation of the TF-IDF scheme, which uses external domain resources as references to calculate the term weighting in a particular domain; document weighting is taken into account in the calculation of term weighting from a group of citations. A simple hierarchical word weighting method is also presented. The work is supported by an underlying architecture for document management using NoSQL databases and employs a simple visualization interface.

Original language	English
Title of host publication	Proceedings of the 5th International Conference on Data Management Technologies and Applications
Publisher	SciTePress
Pages	135-143
ISBN (Print)	9789897581939
DOIs	https://doi.org/10.5220/0005981501350143
Publication status	Published - 31 Dec 2016
Event	5th International Conference on Data Management Technologies and Applications - Lisbon Duration: 24 Jul 2016 → 26 Jul 2016

Conference

Conference	5th International Conference on Data Management Technologies and Applications
City	Lisbon
Period	24/07/16 → 26/07/16
Other	5th International Conference on Data Management Technologies and Applications (24/07/2016-26/07/2016, Lisbon)

Keywords

Data management
Ontology
TF-IDF
Term weighting
Visualization
text mining

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10.5220/0005981501350143

DATA 2016 36Accepted author manuscript, 771 KBLicence: CC BY-NC-ND

https://www.scitepress.org/Link.aspx%3Fdoi%3D10.5220%252f0005981501350143

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Wei, H., Zhao, Y., Liu, E., Wu, S., Deng, Z., Parvinzamir, F., Dong, F., & Clapworthy, G. (2016). Management of scientific documents and visualization of citation relationships using weighted key scientific terms. In Proceedings of the 5th International Conference on Data Management Technologies and Applications (pp. 135-143). SciTePress. https://doi.org/10.5220/0005981501350143

@inproceedings{03739f03fd37475bbb04d6cb342020d0,

title = "Management of scientific documents and visualization of citation relationships using weighted key scientific terms",

abstract = "Effective management and visualization of scientific and research documents can greatly assist researchers by improving understanding of relationships (e.g. citations) between the documents. This paper presents work on the management and visualization of large corpuses of scientific papers in order to help researchers explore their citation relationships. Term selection and weighting are used for mining citation relationships by identifying the most relevant. To this end, we present a variation of the TF-IDF scheme, which uses external domain resources as references to calculate the term weighting in a particular domain; document weighting is taken into account in the calculation of term weighting from a group of citations. A simple hierarchical word weighting method is also presented. The work is supported by an underlying architecture for document management using NoSQL databases and employs a simple visualization interface.",

keywords = "Data management, Ontology, TF-IDF, Term weighting, Visualization, text mining",

author = "Hui Wei and Youbing Zhao and Enjie Liu and Shaopeng Wu and Zhikun Deng and Farzad Parvinzamir and Feng Dong and Gordon Clapworthy",

year = "2016",

month = dec,

day = "31",

doi = "10.5220/0005981501350143",

language = "English",

isbn = "9789897581939",

pages = "135--143",

booktitle = "Proceedings of the 5th International Conference on Data Management Technologies and Applications",

publisher = "SciTePress",

note = "5th International Conference on Data Management Technologies and Applications ; Conference date: 24-07-2016 Through 26-07-2016",

}

Wei, H, Zhao, Y, Liu, E, Wu, S, Deng, Z, Parvinzamir, F, Dong, F & Clapworthy, G 2016, Management of scientific documents and visualization of citation relationships using weighted key scientific terms. in Proceedings of the 5th International Conference on Data Management Technologies and Applications. SciTePress, pp. 135-143, 5th International Conference on Data Management Technologies and Applications, Lisbon, 24/07/16. https://doi.org/10.5220/0005981501350143

Management of scientific documents and visualization of citation relationships using weighted key scientific terms. / Wei, Hui; Zhao, Youbing; Liu, Enjie et al.
Proceedings of the 5th International Conference on Data Management Technologies and Applications. SciTePress, 2016. p. 135-143.

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

TY - GEN

T1 - Management of scientific documents and visualization of citation relationships using weighted key scientific terms

AU - Wei, Hui

AU - Zhao, Youbing

AU - Liu, Enjie

AU - Wu, Shaopeng

AU - Deng, Zhikun

AU - Parvinzamir, Farzad

AU - Dong, Feng

AU - Clapworthy, Gordon

PY - 2016/12/31

Y1 - 2016/12/31

N2 - Effective management and visualization of scientific and research documents can greatly assist researchers by improving understanding of relationships (e.g. citations) between the documents. This paper presents work on the management and visualization of large corpuses of scientific papers in order to help researchers explore their citation relationships. Term selection and weighting are used for mining citation relationships by identifying the most relevant. To this end, we present a variation of the TF-IDF scheme, which uses external domain resources as references to calculate the term weighting in a particular domain; document weighting is taken into account in the calculation of term weighting from a group of citations. A simple hierarchical word weighting method is also presented. The work is supported by an underlying architecture for document management using NoSQL databases and employs a simple visualization interface.

AB - Effective management and visualization of scientific and research documents can greatly assist researchers by improving understanding of relationships (e.g. citations) between the documents. This paper presents work on the management and visualization of large corpuses of scientific papers in order to help researchers explore their citation relationships. Term selection and weighting are used for mining citation relationships by identifying the most relevant. To this end, we present a variation of the TF-IDF scheme, which uses external domain resources as references to calculate the term weighting in a particular domain; document weighting is taken into account in the calculation of term weighting from a group of citations. A simple hierarchical word weighting method is also presented. The work is supported by an underlying architecture for document management using NoSQL databases and employs a simple visualization interface.

KW - Data management

KW - Ontology

KW - TF-IDF

KW - Term weighting

KW - Visualization

KW - text mining

U2 - 10.5220/0005981501350143

DO - 10.5220/0005981501350143

M3 - Conference contribution

SN - 9789897581939

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EP - 143

BT - Proceedings of the 5th International Conference on Data Management Technologies and Applications

PB - SciTePress

T2 - 5th International Conference on Data Management Technologies and Applications

Y2 - 24 July 2016 through 26 July 2016

ER -

Management of scientific documents and visualization of citation relationships using weighted key scientific terms

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