Low-Rank Representations Towards Classification Problem of Complex Networks Karmaşik Aǧlarin Siniflandirma Sorusuna Yönelik Düşük-Dereceli Temsiliyeti

Celik M., TAŞDEMİR A. B., ÖZKAHYA L.

30th Signal Processing and Communications Applications Conference, SIU 2022, Safranbolu, Türkiye, 15 - 18 Mayıs 2022 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu55565.2022.9864691
  • Basıldığı Şehir: Safranbolu
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: Graph embeddings, graph representations, low-dimensional embedding, low-rank representation
  • Hacettepe Üniversitesi Adresli: Evet

Özet

© 2022 IEEE.Complex networks representing social interactions, brain activities, molecular structures have been studied widely to be able to understand and predict their characteristics as graphs. Models and algorithms for these networks are used in real-life applications, such as search engines, and recommender systems. In general, such networks are modelled by constructing a low-dimensional Euclidean embedding of the vertices of the network, where proximity of the vertices in the Euclidean space hints the likelihood of an edge (link). In this work, we study the performance of such low-rank representations of real-life networks on a network classification problem.