Topic-aware visual citation tracing via enhanced term weighting for efficient literature retrieval

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

doi:10.1007/978-3-319-62911-7_5

Topic-aware visual citation tracing via enhanced term weighting for efficient literature retrieval

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

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

Abstract

© Springer International Publishing AG 2017. Efficient retrieval of scientific literature related to a certain topic plays a key role in research work. While little has been done on topic-enabled citation filtering in traditional citation tracing, this paper presents visual citation tracing of scientific papers with document topics taken into consideration. Improved term selection and weighting are employed for mining the most relevant citations. A variation of the TF-IDF scheme, which uses external domain resources as references is proposed to calculate the term weighting in a particular domain. Moreover document weight is also incorporated in the calculation of term weight from a group of citations. A simple hierarchical word weighting method is also presented to handle keyword phrases. A visual interface is designed and implemented to interactively present the citation tracks in chord diagram and Sankey diagram.

Original language	English
Title of host publication	Communications in Computer and Information Science
Publisher	Springer-Verlag
Pages	79-101
Number of pages	23
ISBN (Print)	9783319629100
DOIs	https://doi.org/10.1007/978-3-319-62911-7_5
Publication status	Published - 2017
Externally published	Yes

Publication series

Name	Communications in Computer and Information Science
Volume	737

Keywords

Citation tracing
Data management
Ontology
TF-IDF
Term weighting
Text mining
Visualization

Access to Document

10.1007/978-3-319-62911-7_5

http://www.mendeley.com/research/topicaware-visual-citation-tracing-via-enhanced-term-weighting-efficient-literature-retrieval

Cite this

Zhao, Y., Wei, H., Wu, S., Parvinzamir, F., Deng, Z., Zhao, X., Ersotelos, N., Dong, F., Clapworthy, G., & Liu, E. (2017). Topic-aware visual citation tracing via enhanced term weighting for efficient literature retrieval. In Communications in Computer and Information Science (pp. 79-101). (Communications in Computer and Information Science; Vol. 737). Springer-Verlag. https://doi.org/10.1007/978-3-319-62911-7_5

Zhao, Youbing ; Wei, Hui ; Wu, Shaopeng ; Parvinzamir, Farzad ; Deng, Zhikun ; Zhao, Xia ; Ersotelos, Nikolaos ; Dong, Feng ; Clapworthy, Gordon ; Liu, Enjie. / Topic-aware visual citation tracing via enhanced term weighting for efficient literature retrieval. Communications in Computer and Information Science. Springer-Verlag, 2017. pp. 79-101 (Communications in Computer and Information Science).

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abstract = "{\textcopyright} Springer International Publishing AG 2017. Efficient retrieval of scientific literature related to a certain topic plays a key role in research work. While little has been done on topic-enabled citation filtering in traditional citation tracing, this paper presents visual citation tracing of scientific papers with document topics taken into consideration. Improved term selection and weighting are employed for mining the most relevant citations. A variation of the TF-IDF scheme, which uses external domain resources as references is proposed to calculate the term weighting in a particular domain. Moreover document weight is also incorporated in the calculation of term weight from a group of citations. A simple hierarchical word weighting method is also presented to handle keyword phrases. A visual interface is designed and implemented to interactively present the citation tracks in chord diagram and Sankey diagram.",

keywords = "Citation tracing, Data management, Ontology, TF-IDF, Term weighting, Text mining, Visualization",

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

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language = "English",

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Zhao, Y, Wei, H, Wu, S, Parvinzamir, F, Deng, Z, Zhao, X, Ersotelos, N, Dong, F, Clapworthy, G & Liu, E 2017, Topic-aware visual citation tracing via enhanced term weighting for efficient literature retrieval. in Communications in Computer and Information Science. Communications in Computer and Information Science, vol. 737, Springer-Verlag, pp. 79-101. https://doi.org/10.1007/978-3-319-62911-7_5

Topic-aware visual citation tracing via enhanced term weighting for efficient literature retrieval. / Zhao, Youbing; Wei, Hui; Wu, Shaopeng; Parvinzamir, Farzad; Deng, Zhikun; Zhao, Xia; Ersotelos, Nikolaos; Dong, Feng; Clapworthy, Gordon; Liu, Enjie.

Communications in Computer and Information Science. Springer-Verlag, 2017. p. 79-101 (Communications in Computer and Information Science; Vol. 737).

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

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AU - Zhao, Youbing

AU - Wei, Hui

AU - Wu, Shaopeng

AU - Parvinzamir, Farzad

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AU - Zhao, Xia

AU - Ersotelos, Nikolaos

AU - Dong, Feng

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