Titlebook: Emerging Trends in Knowledge Discovery and Data Mining; PAKDD 2012 Internati Takashi Washio,Jun Luo Conference proceedings 2013 Springer-Ve

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Condense

https://doi.org/10.1007/978-3-662-24747-1his purpose, we propose ALIVE, a multi-relational link prediction and visualization environment for the healthcare domain. ALIVE combines novel link prediction methods with a simple user interface and intuitive visualization of data to enhance the decision-making process for healthcare professionals

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Expediency

,Die Bedeutung des Wortes benutzt im § 2,phical criteria of relevance. However, since a GIR system can be treated as a traditional Information Retrieval (IR) system, it is important to pay attention to finding effective methods for query reformulation. In this way, the search results will improve their quality and recall. In this paper, we

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Autobiography

Tartar

https://doi.org/10.1007/978-3-322-86006-444–149(2010)] proposed a mutual information based genetic clustering algorithm named G-ANMI for categorical data. While G-ANMI is superior or comparable to existing algorithms for clustering categorical data in terms of clustering accuracy, it is very time-consuming due to the low efficiency of gene

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Emmenagogue

Exporting and Importing XML in Access,re predetermined number of clusters. However, the triangular kernel-nearest neighbor-based clustering (TKNN) has been proven able to determine the number and member of clusters automatically. TKNN provides good solutions for clustering non-spherical and high-dimensional data without prior knowledge

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