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Piecewise Maximal Similarity for Ad-hoc Social Networks

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Abstract

Computing Profile Similarity is a fundamental requirement in the area of Social Networks to suggest similar social connections that have high chance of being accepted as actual connection. Representing and measuring similarity appropriately is a pursuit of many researchers. Cosine similarity is a widely used metric that is simple and effective. This paper provides analysis of cosine similarity for social profiles and proposes a novel method to compute Piecewise Maximal Similarity between profiles. The proposed metric is 6% more effective to measure similarity than cosine similarity based on computations on real data.

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Authors and Affiliations

  1. Department of Computer Engineering, YMCA University of Science and Technology, Faridabad, India

    Sapna Gambhir & Nagender Aneja

  2. Faculty of Integrated Technologies, Universiti Brunei Darussalam, Gadong, Brunei Darussalam

    Liyanage Chandratilake De Silva

Authors
  1. Sapna Gambhir
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  2. Nagender Aneja
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  3. Liyanage Chandratilake De Silva
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Correspondence to Nagender Aneja.

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Gambhir, S., Aneja, N. & De Silva, L.C. Piecewise Maximal Similarity for Ad-hoc Social Networks. Wireless Pers Commun 97, 3519–3529 (2017). https://doi.org/10.1007/s11277-017-4683-4

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  • DOI: https://doi.org/10.1007/s11277-017-4683-4

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