Management of Scientific Documents and Visualization of Citation Relationships using Weighted Key Scientific Terms

Wei, Hui; Zhao, Youbing; Xu, Haiqin; Deng, Zhikun; Parvinzamir, Farzad; Dong, Feng; Liu, Enjie; Clapworthy, Gordon

doi:10.5220/0005981501350143

Cited by 5 publications

(3 citation statements)

References 6 publications

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“…The future work will focus on integrating the risk evaluation diagram and the healthlines to achieve time-varying risk assessment. It is also highly desirable to assist the manual risk extraction with automatic text mining, such as the techniques proposed in Dr Inventor (Wei et al 2016).…”

Section: Discussionmentioning

confidence: 99%

Integrated visualisation of wearable sensor data and risk models for individualised health monitoring and risk assessment to promote patient empowerment

Zhao

Parvinzamir

Wilson

et al. 2016

J Vis

Self Cite

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Patient empowerment delivers health and social care services that enable people to gain more control of their healthcare needs. With the advancement of sensor technologies, it is increasingly possible to monitor people's health with dedicated wearable sensors. The consistent measurements from a variety of wearable sensors imply that a huge amount of data may be exploited to monitor and predict people's health using medically proven models. In the process of health data representation and analysis, visualisation can be employed to promote data analysis and knowledge discovery via mature visual paradigms and welldesigned user interactions. In this paper, we introduce the role of visualisation for individualised health monitoring and risk management in the background of a European Commission funded project, which aims to provide self-management of cardiorenal diseases with the assistance of wearable sensors. The DOI 10.1007/s12650-016-0402-6 visualisation components of health monitoring, risk model exploration, and risk analysis are presented to achieve personalised health and risk monitoring and to promote people's wellbeing. It allows the patients not only to view existing risks, but also to gain awareness of the right pathway to change their lifestyles in order to reduce potential health risks.

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Section: Discussionmentioning

confidence: 99%

Integrated visualisation of wearable sensor data and risk models for individualised health monitoring and risk assessment to promote patient empowerment

Zhao

Parvinzamir

Wilson

et al. 2016

J Vis

Self Cite

View full text Add to dashboard Cite

show abstract

“…In PyGraphviz [10], a graph was created to represent the evolutionary process of the deep learning field in the last 25 years. Wei et al [2] propose an interactive visualization method that uses citation paths [11]. Berger et al [12] treat the documents as a collection of special words.…”

Section: Related Workmentioning

confidence: 99%

“…In [9], [10] it is difficult to visually obtain a sequence of closely related works due to the number of relationships presented. In [2], [6]- [8], [16], the opinion or change of opinion of the specialist is not considered in the classification of key references. Finally, in [18], the user cannot easily filter the citation links of a certain paper sorted by relevance, to reduce visual clutter and find relevant or influential citation paths.…”

Section: Related Workmentioning

confidence: 99%

A Collaborative Support for Recommending References in Papers

Guilarte

Barbosa

Pesco

2019

Anais Estendidos Do XXXII Conference on Graphics, Patterns and Images (SIBRAPI Estendido 2019)

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Understanding citations to scientific publications is a task of vital importance in the academic world. This task can be supported by appropriate data structures and visualization mechanisms. One challenge is the amount of existing relationships and the difficulty of determining which of the references of a document are considered the most potentially relevant to it. In this paper, we propose a visual approach based on graphs to recommend important references. Also, we propose a procedure to build and update the citation graph in a collaborative way.

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Topic-Aware Visual Citation Tracing via Enhanced Term Weighting for Efficient Literature Retrieval

Zhao

Wei

et al. 2017

Communications in Computer and Information Science

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Management of Scientific Documents and Visualization of Citation Relationships using Weighted Key Scientific Terms

Cited by 5 publications

References 6 publications

Integrated visualisation of wearable sensor data and risk models for individualised health monitoring and risk assessment to promote patient empowerment

Integrated visualisation of wearable sensor data and risk models for individualised health monitoring and risk assessment to promote patient empowerment

A Collaborative Support for Recommending References in Papers

Topic-Aware Visual Citation Tracing via Enhanced Term Weighting for Efficient Literature Retrieval

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