Artur Abdullin

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This paper tackles the issue of building a large-scale virtual organization for individuals and institutions that are associated with the field of computational intelligence (CI) and machine learning (ML). It begins with a few scenarios that will help illustrate the need for a virtual community in CIML.
Recent years have seen an increasing interest in clustering data comprising multiple domains or modalities, such as categorical, numerical and transactional, etc. This kind of data is sometimes found within the context of clustering multiview, heterogeneous, or multimodal data. Traditionally, different types of attributes or domains have been handled by(More)
We propose a semi-supervised framework to handle diverse data formats or data with mixedtype attributes. Our preliminary results in clustering data with mixed numerical and categorical attributes show that the proposed semi-supervised framework gives better clustering results in the categorical domain. Thus the seeds obtained from clustering the numerical(More)
Serial histological assays of lymph nodes removed during extensive lymphadenectomy not infrequently reveal metastases, in case of gastric cancer, in paraaortic lymph nodes and the nodes located along the celiac trunk, splenic and hepatic vessels. Among 35 patients 19 showed metastases in these nodes. Metastases were detected also in cases when lymphnodes of(More)