Developing Horizon Scanning Methods for the Discovery of Scientific Trends

@article{Karasalo2019DevelopingHS,
  title={Developing Horizon Scanning Methods for the Discovery of Scientific Trends},
  author={Maja Karasalo and Johan Schubert},
  journal={2019 International Conference on Document Analysis and Recognition (ICDAR)},
  year={2019},
  pages={1055-1062}
}
  • Maja KarasaloJ. Schubert
  • Published 1 September 2019
  • Computer Science
  • 2019 International Conference on Document Analysis and Recognition (ICDAR)
In this application-oriented paper, we develop a methodology and a system for horizon scanning of scientific literature to discover scientific trends. Literature within a broadly defined field is automatically clustered and ranked based on topic and scientific impact, respectively. A method for determining the optimal number of clusters for the established Gibbs sampling Dirichlet multinomial mixture model (GSDMM) algorithm is proposed along with a method for deriving descriptive and… 

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References

SHOWING 1-7 OF 7 REFERENCES

A review of theory and practice in scientometrics

Internal versus External cluster validation indexes

A comparison between external and internal indexes is shown and results obtained indicate that internal indexes are more accurate in group determining in a given clustering structure.

Text Classification from Labeled and Unlabeled Documents using EM

This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents, and presents two extensions to the algorithm that improve classification accuracy under these conditions.

Constructing and evaluating alternative frames of discernment

A Mathematical Theory of Communication

It is proved that the authors can get some positive data rate that has the same small error probability and also there is an upper bound of the data rate, which means they cannot achieve the data rates with any encoding scheme that has small enough error probability over the upper bound.

A dirichlet multinomial mixture model-based approach for short text clustering

This paper proposed a collapsed Gibbs Sampling algorithm for the Dirichlet Multinomial Mixture model for short text clustering and found that GSDMM can infer the number of clusters automatically with a good balance between the completeness and homogeneity of the clustering results, and is fast to converge.

An information fusion demonstrator for tactical intelligence processing in network-based defense