阐释
发表于 2025-3-30 10:21:32
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doxazosin
发表于 2025-3-30 16:26:59
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Commonwealth
发表于 2025-3-30 18:10:19
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Proponent
发表于 2025-3-31 00:45:27
Downloading and Installing OpenStack Trove,y-driven search system based on Web services. The Knowledge Sifter architecture is extended to include a case-based methodology for collaborative semantic search, including case creation, indexing and retrieval services. A collaborative filtering methodology is presented that uses stored cases as a
放牧
发表于 2025-3-31 04:31:36
The Magnificent Internet Protocol, view, these local approximations can take a role similar to the global approximations built by eager learning methods. Thus, we propose that local approximations can be interpreted either as: 1) a symbolic similitude among a set of cases, 2) a partial domain model, or 3) an explanation of the syste
interrogate
发表于 2025-3-31 07:09:51
https://doi.org/10.1007/978-1-4842-1814-3ones for estimating their similarity. If word . co-occurs with word ., we say . and . share a first order association between them. If . co-occurs with . in some documents, and . with . in some others, then . and . are said to share a second order co-occurrence via .. Higher orders of co-occurrence
gusher
发表于 2025-3-31 12:06:28
https://doi.org/10.1007/978-1-4842-1833-4er, we argue that label ranking is an amenable task from a CBR point of view and, in particular, is more amenable to supporting case-based problem solving than standard classification. Moreover, by developing a case-based approach to label ranking, we will show that, the other way round, concepts an
Ingredient
发表于 2025-3-31 15:34:28
https://doi.org/10.1007/978-1-4842-1833-4struct the case base invariably contains erroneous, noisy cases. Automated removal of these noisy cases can improve system accuracy. In addition, error rates for nearest neighbour classifiers can often be reduced by removing cases to give smoother decision boundaries between classes. In this paper w
implore
发表于 2025-3-31 18:54:13
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lavish
发表于 2025-3-31 21:49:52
S G Ganesh,Hari Kiran,Tushar Sharmam them. Although the computational time is improved, the accuracy rate may be degraded if the clusters are not representative enough due to data geometry. This paper proposes a methodology for allowing the expert to analyze the case retrieval strategies from a clustered case memory according to the