亲属
发表于 2025-3-28 15:34:23
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IRK
发表于 2025-3-28 21:59:42
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考博
发表于 2025-3-29 01:01:15
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MAUVE
发表于 2025-3-29 06:13:35
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patriarch
发表于 2025-3-29 10:14:34
Visually Summarizing Semantic Evolution in Document Streams with Topic Tableopic within the collection, the words characterizing this topic, the semantic changes of a topic from one timepoint to the next. As an example, we visualize content of the NIPS proceedings from 1987 to 1999.
Painstaking
发表于 2025-3-29 11:56:36
Testing and Improving the Performance of SVM Classifier in Intrusion Detection Scenario work also evaluates the performance of other learning techniques (Filtered J48 clustering, Naïve Bayes) over benchmark intrusion detection dataset for being complementary of SVM. The model generation is computation intensive; hence to reduce the time required for model generation various different
知识分子
发表于 2025-3-29 17:29:04
Modeling the International Classification of Diseases (ICD-10) in OWLility and data integration of several medical resources such as ICD. Our resulting model captures the hierarchical information of the ICD-10 as well as comprehensive class labels for English and German. Specialities such as “Exclusion” statements, which make statements about the disjointness of cert
构想
发表于 2025-3-29 21:13:37
Improving the Semantics of a Conceptual Schema of the Human Genome by Incorporating the Modeling ofto show how conceptual modeling techniques applied to human genome concepts can help to disambiguate and correctly represent the relevant concepts in a conceptual schema, thereby achieving a deeper and more adequate understanding of the domain.
Kidney-Failure
发表于 2025-3-30 00:12:57
Semantic Web Search System Founded on Case-Based Reasoning and Ontology Learningontologies by using previous search queries performed by the user. Some experiments and results obtained with the proposed system are also presented, which show an improvement on the precision of the Web search and ontology enrichment.
Epithelium
发表于 2025-3-30 05:04:04
A Connection between Extreme Learning Machine and Neural Network Kernel the number of hidden units, as is the current practice, but also the variance of weights. We also study the interaction of variance and the number of hidden units, and discuss some properties of ELM, that may have been too strongly interpreted previously.