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used for further learning such as
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example-based learning
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and group learn - ing . The burden
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training data . Rule-based and
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example-based learning
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algorithms are suitable to this
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7 . 3.2 Example-based learning
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Example-based learning
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is suitable for classification
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domain are shown in Figure 7 . 3.2
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Example-based learning
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Example-based learning is suitable
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W02-1808 |
examine the effectiveness of an
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example-based learning
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approach to resolve found ambiguities
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N06-1016 |
function relied on the nature of the
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example-based learning
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method , which made their example
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P97-1055 |
especially obvious in the context of
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example-based learning
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techniques , where the inference
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especially obvious in the context of
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example-based learning
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techniques , where the inference
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resource for statistical analysis and
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example-based learning
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. <title></title> <authors></authors>
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the agent teaching process , the
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example-based learning
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method is invoked . In this process
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probabilistic segmentation and a case - or
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example-based learning
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approach ( Kit et al. , 2002
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W02-1808 |
memory-based , instance-based or
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example-based learning
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, has been popular for various
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acquire word clusters Incremental
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example-based learning
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algorithms , like COBWEB Fisher
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baselines : ( 1 ) SVM , ( 2 ) Positive
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Example-Based Learning
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( PEBL ) proposed by ( Yu et
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this is not to be mistaken for
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example-based learning
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techniques to perform automatic
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be exploited .5 To determine 5
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Example-based learning
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has also been applied succesfully
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another . We used a version of
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example-based learning
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to determine whether these tagger
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case-based , mem - ory-based , and
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example-based learning
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) , generalization happens at
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task Formally , the problem of
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example-based learning
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of WSD models can be stated as
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for generating training data for
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example-based learning
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( it can also take input from
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