Three-Way Analysis for a Better Understanding of Word Embedding Models. - Elekes, Ábel (2021)

How meaningful are similarities in deep trajectory representations? - Taghizadeh, Saeed; Elekes, Ábel; Schäler, Martin; Böhm, Klemens (Inf. Syst., 2021)

Visit Places on Your Way: A Skyline Approach in Time-Dependent Networks. - Taghizadeh, Saeed; Elekes, Ábel; Schäler, Martin (2021)

Toward meaningful notions of similarity in NLP embedding models. - Elekes, Ábel; Englhardt, Adrian; Schäler, Martin; Böhm, Klemens (Int. J. Digit. Libr., 2020)

Learning from Few Samples: Lexical Substitution with Word Embeddings for Short Text Classification. - Elekes, Ábel; Stefano, Antonino Simone Di; Schäler, Martin; Böhm, Klemens; Keller, Matthias (2019)

Resources to Examine the Quality of Word Embedding Models Trained on n-Gram Data. - Elekes, Ábel; Englhardt, Adrian; Schäler, Martin; Böhm, Klemens (2018)

On the Various Semantics of Similarity in Word Embedding Models. - Elekes, Ábel; Schäler, Martin; Böhm, Klemens (2017)