• Corpus ID: 233346991

Combining dissimilarity measure for the study of evolution in scientific fields

@article{Zheng2021CombiningDM,
  title={Combining dissimilarity measure for the study of evolution in scientific fields},
  author={Lukun Zheng and Yuhang Jiang},
  journal={ArXiv},
  year={2021},
  volume={abs/2104.10996}
}
The evolution of scientific fields has been attracting much attention in recent years. One of the key issues in evolution of scientific field is to quantify the dissimilarity between two collections of scientific publications in literature. Many existing works study the evolution based on one or two dissimilarity measures, despite the fact that there are many different dissimilarity measures. Finding the appropriate dissimilarity measures among such a collection of choices is of fundamental… 
1 Citations

Figures and Tables from this paper

The Use of Dissimilarity Measures for the Study of Evolution in Scientific Fields

  • Lukun Zheng
  • Education
    Global Journal of Engineering Sciences
  • 2021
One of the key issues in evolution of scientific field is to quantify the dissimilarity between two collections of scientific publications in literature. Many existing works study the evolution based

References

SHOWING 1-10 OF 41 REFERENCES

Using text analysis to quantify the similarity and evolution of scientific disciplines

An analysis of almost 20 M papers from the past three decades reveals that the linguistic similarity is related but different from experts and citation-based classifications, leading to an improved view on the organization of science.

On the time evolution of received citations, in different scientific fields: An empirical study

Showing the Essential Science Structure of a Scientific Domain and its Evolution

This article presents the scientogram of the United States for the year 2002, identifying its essential structure and tries to detect patterns and tendencies in the three scientograms that would allow one to predict or flag the evolution of a scientific domain.

Understanding the evolution of multiple scientific research domains using a content and network approach

Experimental results on DBLP data related to IR, DB, and W3 domains showed that the W3 domain was getting closer to both IR andDB whereas the distance between IR and DB remained relatively constant.

The evolution of citation graphs in artificial intelligence research

A bibliometric analysis of the past and present of AI research suggests a consolidation of research influence, which may present challenges for the exchange of ideas between AI and the social sciences.

Research Front Detection and Topic Evolution Based on Topological Structure and the PageRank Algorithm

The experiment’s results show that the proposed approach can obtain reasonable clustering results, and it is effective for research front detection and topic evolution.

Evaluation of the evolution of relationships between topics over time

Information clustering based on content-(dis)similarity of the underlying textual material and graph-theoretical considerations to deal with the network of relationships between content-similar topics are described and combined in a new approach.

Using time-series similarity measures to compare animal movement trajectories in ecology

Five commonly used measures of trajectory similarity are introduced: dynamic time warping, longest common subsequence (LCSS), edit distance for real sequences (EDR), Fréchet distance and nearest neighbour distance and NND, of which only NND is routinely used by ecologists.