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Friendship prediction in social networks using developed extreme learning machine with Kernel reduction and probabilistic calculation

Abd. Alkhalec Tharwat, Muhammed E. and Md. Fudzee, Mohd. Farhan and Kasim, Shahreen and Ramli, Azizul Azhar and Madni, Syed Hamid Hussain (2022) Friendship prediction in social networks using developed extreme learning machine with Kernel reduction and probabilistic calculation. In: Recent Advances in Soft Computing and Data Mining Proceedings of the Fifth International Conference on Soft Computing and Data Mining (SCDM 2022), May 30-31, 2022. Lecture Notes in Networks and Systems, 457 (NA). Springer Science and Business Media Deutschland GmbH, Cham, Switzerland, pp. 56-68. ISBN 978-303100827-6

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Official URL: http://dx.doi.org/10.1007/978-3-031-00828-3_6

Abstract

The social network remains a highly dynamic object. Friendship prediction presents a significant problem in the research in network application in general and in social networking applications in particular. It involves analyzing an existing network graph and predicting more links inside the graph that were not identified before. Various models and approaches were developed for this purpose. Similarity-based models were used extensively, mainly they suffered from non-capability of handling the changing nature of the graph. Other models have supervised models that require training on labelled data. However, they need the extraction of many features to achieve satisfying performance. This work provides a novel implicit link prediction probabilistic reduced kernel extreme learning machine named ILP-PRKELM. Unlike the traditional supervised model of link prediction, ILP-PRKELM is attributed to the capability of achieving absolute accuracy with less number of features. Experimental results showed the superiority of ILP-PRKELM with an accomplished accuracy of 84.6 and 78.6 for Last.fm and Douban respectively, which is equivalent to 2% improved accuracy over the benchmarks.

Item Type:Book Section
Uncontrolled Keywords:explicit relationship, extreme learning machine, friend relationship, implicit relationship, link prediction, social network
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computing
ID Code:101091
Deposited By: Yanti Mohd Shah
Deposited On:01 Jun 2023 07:31
Last Modified:01 Jun 2023 07:31

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