Starosta, BartłomiejKłopotek, Mieczysław A.Wierzchoń, Sławomir T.2023-09-212023-09-212023Starosta B., Kłopotek M.A., Wierzchoń S.T., Hashtag Similarity Based on Laplacian Eigenvalue Spectrum. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 113-118, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.16.978-83-66741-92-8http://hdl.handle.net/11652/4791https://doi.org/10.34658/9788366741928.16Hashtags play nowadays an important role in the current social media world. They are usually deemed to represent topics of e.g. tweets. As the number of hashtags is growing, an overview of the information flow requires some method of grouping these hashtags. The grouping requires a similarity measure. In this paper we propose a novel measure of similarity between hashtags based on the Graph Spectral Analysis.enDla wszystkich w zakresie dozwolonego użytkuFair use conditiongraph spectral analysiscombinatorial graph Laplacianeigenvalue spectrogram based similarityartificial intelligencewykres analizy spektralnejkombinatoryczny wykres Laplacianapodobieństwo oparte na spektrogramie wartości własnychsztuczna inteligencjaRozdział - monografiaLicencja PŁLUT License10.34658/9788366741928.16