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. Copyright © 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.
|Title of host publication||Proceedings of the 5th International Conference on Data Management Technologies and Applications|
|Publisher||SCITEPRESS - Science and Technology Publications|
|Number of pages||9|
|Publication status||Published - 2016|
|Name||Proceedings of the 5th International Conference on Data Management Technologies and Applications|
Wei, H., Zhao, Y., Wu, S., Deng, Z., Parvinzamir, F., Dong, F., Liu, E., & 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). (Proceedings of the 5th International Conference on Data Management Technologies and Applications). SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0005981501350143