• Simulating the Role of Norms in Processes of Social Innovation: Three Case Studies 

  Jager, Wander; Guijarro-Berdiñas, Bertha; Bouman, Loes; Antosz, Patrycja; Alonso-Betanzos, Amparo; Salt, Douglas; Polhill, J. Gary; Rodríguez Arias, Alejandro; Sánchez-Maroño, Noelia (SimSoc Consortium, 2024-01)

  [Absctract]: Norms and values are critical drivers in social innovation processes, such as community projects on sustainable energy. Simulating such processes could help uncover conditions that support these social ...

• Insights into distributed feature ranking 

  Bolón-Canedo, Verónica; Sechidis, Konstantinos; Sánchez-Maroño, Noelia; Alonso-Betanzos, Amparo; Brown, Gavin (Elsevier, 2019)

  [Abstract]: In an era in which the volume and complexity of datasets is continuously growing, feature selection techniques have become indispensable to extract useful information from huge amounts of data. However, existing ...

• A scalable decision-tree-based method to explain interactions in dyadic data 

  Eiras-Franco, Carlos; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo; Bahamonde, Antonio (Elsevier, 2019-12)

  [Abstract]: Gaining relevant insight from a dyadic dataset, which describes interactions between two entities, is an open problem that has sparked the interest of researchers and industry data scientists alike. However, ...

• Fast Distributed kNN Graph Construction Using Auto-tuned Locality-sensitive Hashing 

  Eiras-Franco, Carlos; Martínez Rego, David; Kanthan, Leslie; Piñeiro, César; Bahamonde, Antonio; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo (Association for Computing Machinery, 2020)

  [Abstract]: The k-nearest-neighbors (kNN) graph is a popular and powerful data structure that is used in various areas of Data Science, but the high computational cost of obtaining it hinders its use on large datasets. ...

• Community detection and social network analysis based on the Italian wars of the 15th century 

  Fumanal-Idocin, Javier; Alonso-Betanzos, Amparo; Cordón, Oscar; Bustince, Humberto; Minárová, Mária (Elsevier, 2020)

  [Abstract]: In this contribution we study social network modelling by using human interaction as a basis. To do so, we propose a new set of functions, affinities, designed to capture the nature of the local interactions ...

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