COMPARISON OF SIMILARITY AND DISSIMILARITY FOR INFORMATION RETRIEVAL
DOI:
https://doi.org/10.17605/OSF.IO/M7GNTKeywords:
COMPARISON OF SIMILARITY AND DISSIMILARITY FOR INFORMATION RETRIEVALAbstract
v
Downloads
References
Apparicio P, Abdelmajid M, Riva M, Shearmur R. Comparing alternative approaches to measuring the geographical accessibility of urban health services: Distance types and aggregation-error issues. International Journal of Health Geographics.. Chen, B. Mulgrew, and P. M. Grant, “A clustering technique for digital communications channel equalization using radial basis function networks,” IEEE Trans. on Neural Networks, vol. 4, pp. 570-578, July 1993.
https://slidewiki.org/print/1265/data-mining/1280-2/2.
Baroni-Urbani, C., Buser, M.W., (1976), “Similarity of Binary Data”
Shirkhorshidi AS, Aghabozorgi S, Wah TY, Herawan T. Big Data Clustering: A Review Computational Science and Its Applications.
Aczél J, Saaty TL Procedures for synthesizing ratio judgements. J Math Psychol.
Balakrishnan V, Sanghvi LD Distance between populations on the basis of attribute data. Biometrics.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.