Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: International Workshop “Hybrid methods of modeling and optimization in complex systems” (HMMOCS 2022); Krasnoyarsk; Krasnoyarsk
Год издания: 2022
Идентификатор DOI: 10.15405/epct.23021.42
Ключевые слова: olap, hypercube, FASMI, multi-dimensional structure, analytics
Аннотация: The purpose of this work is to develop the structure of the algorithm for automatic grouping (clustering) of 3D model metadata which may include model name, dimensions, file size, file format, keywords etc. The relevance of this work is determined by the need for companies to process complexly structured data, in particular 3D modeПоказать полностьюls, and detect groups of similar 3D models for forming their catalogues and other purposes. "similarity", we mean the proximity of objects in a multidimensional space of features, and the problem is reduced to partitioning this space into subspaces of objects so that the objects located in the subspaces form homogeneous groups. We propose an algorithm for automatic grouping of the 3D models based on their metadata, which enables us to group objects according to their numeric and categorical characteristics. The experiments were carried out with the involvement of experts, their evaluation showed the high efficiency of the developed method.
Журнал: HYBRID METHODS OF MODELING AND OPTIMIZATION IN COMPLEX SYSTEMS
Номера страниц: 343-350
Место издания: London, United Kingdom
Издатель: European Proceedings