Full-Text Clustering Methods for Current Research Directions Detection

Authors

Grigoriev O. Devyatkin D.

Annotation

The paper contains a brief overview of full-text clustering methods for current research directions detection. A novel full-text clustering method is proposed. A dataset is created and experimental results are verified by problem domain “Regenerative medicine” experts with PhD degrees. The proposed method is well applicable for research directions detection according to experimental results. Finally, prospects and drawbacks of the proposed method are discussed.

External links

Download PDF at CEUR Workshop Proceedings: http://ceur-ws.org/Vol-1536/paper23.pdf

Download PDF or read online at ResearchGate: https://www.researchgate.net/publication/299511049_Full-Text_Clustering_Methods_for_Current_Research_Directions_Detection

Semantic Scholar: https://api.semanticscholar.org/CorpusID:14980267

Reference link

Devyatkin D. et al. Full-Text Clustering Methods for Current Research Directions Detection // DAMDID/RCDL. – 2015. – p. 152-156