Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/de-gruyter/topological-and-attribute-link-prediction-using-firefly-algorithm-IS4txzwf2x
References (26)
-
Alexis Papadimitriou, P. Symeonidis, Y. Manolopoulos (2012)
Fast and accurate link prediction in social networking systemsJ. Syst. Softw., 85
-
Xin-She Yang (2008)
Nature-Inspired Metaheuristic Algorithms -
Hanghang Tong, C. Faloutsos, Y. Koren (2007)
Fast direction-aware proximity for graph mining -
R. Hanneman (2001)
Introduction to Social Network Methods -
Rajeev Atla, Quentin Dubroff (1987)
Random walks and electric networksAmerican Mathematical Monthly, 94
-
P. Jaccard
Etude comparative de la distribution florale dans une portion des Alpes et des Jura, 37
-
E. Leicht, P. Holme, Mark Newman (2005)
Vertex similarity in networks.Physical review. E, Statistical, nonlinear, and soft matter physics, 73 2 Pt 2
-
Lada Adamic, Eytan Adar (2003)
Friends and neighbors on the WebSoc. Networks, 25
-
T. Sørensen, T. Sørensen, T. Biering-Sørensen, Tia Sørensen, J. Sorensen (1948)
A method of establishing group of equal amplitude in plant sociobiology based on similarity of species content and its application to analyses of the vegetation on Danish commons -
M. Hasan, Mohammed Zaki (2011)
A Survey of Link Prediction in Social Networks -
General Terms Algorithms -
H. Song, T. Cho, Vacha Dave, Yin Zhang, L. Qiu (2009)
Scalable proximity estimation and link prediction in online social networks -
L. Katz (1953)
A new status index derived from sociometric analysisPsychometrika, 18
-
E. Ravasz, A. Somera, D. Mongru, Z. Oltvai, A. Barabási (2002)
Hierarchical Organization of Modularity in Metabolic NetworksScience, 297
-
Gerard Salton, Michael McGill (1983)
Introduction to Modern Information Retrieval -
Ehsan Sherkat, Maseud Rahgozar, M. Asadpour (2015)
Structural link prediction based on ant colony approach in social networksPhysica A-statistical Mechanics and Its Applications, 419
-
Glen Jeh, J. Widom (2002)
SimRank: a measure of structural-context similarityProceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
-
Weiping Liu, Linyuan Lü (2010)
Link prediction based on local random walkEPL (Europhysics Letters), 89
-
Jia-Yu Pan, Hyung-Jeong Yang, C. Faloutsos, P. Sahin (2004)
Automatic multimedia cross-modal correlation discoveryProceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
-
Bolun Chen, Ling Chen (2014)
A link prediction algorithm based on ant colony optimizationApplied Intelligence, 41
-
Zan Huang, Xin Li, Hsinchun Chen (2005)
Link prediction approach to collaborative filteringProceedings of the 5th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL '05)
-
EPJ manuscript No. (will be inserted by the editor) Predicting Missing Links via Local Information -
Linyuan Lu, Tao Zhou (2010)
Link Prediction in Complex Networks: A SurveyArXiv, abs/1010.0725
-
(2005)
ChenH., Link prediction approach to collaborative filtering, in Proceedings of the 5th ACM/IEEE-CS joint conference on -
Víctor Martínez, F. Berzal, J. Cubero (2016)
A Survey of Link Prediction in Complex NetworksACM Computing Surveys (CSUR), 49
-
François Lorrain, H. White (2022)
“Structural Equivalence of Individuals in Social Networks”The SAGE Encyclopedia of Research Design
- Publisher
- de Gruyter
- Copyright
- © 2020 Srilatha Pulipati et al., published by De Gruyter
- eISSN
- 2299-1093
- DOI
- 10.1515/comp-2020-0001
- Publisher site
- See Article on Publisher Site
Abstract
AbstractLink prediction problem has received remarkable interest in recent past. In this paper, firefly swarm intelligence algorithm is used to perform link prediction exploiting the topological and node attribute features of social network. Fireflies will be made to traverse on nodes and edges of social networks and the brightness of fireflies will play a major role in their movement. Common neighbor method of link prediction is used to compute similarity score upon each iteration. Performance of the proposed algorithm were analyzed over standard data sets using validation method called ten-fold method. The accuracy of proposed work is measured in terms of Area Under the Curve Characteristics (AUC), Recall and Precision. Experimental results showed that the proposed work outperforms the methods proposed in the literature.
Journal
Open Computer Science – de Gruyter
Published: Jan 1, 2020