| H05-1076 | Acquired Answer Patterns The answer | pattern acquisition algorithm | returns multiple answer patterns |
| W06-0207 | found by the Corpus Analyser . The | pattern acquisition algorithm | presented earlier is implemented |
| P03-1044 | method differs from the previous | pattern acquisition algorithms | in that it introduces competition |
| W06-2207 | patterns . It is the task of the | pattern acquisition algorithm | to extract only the relevant |
| W04-1204 | the testing phase . Because the | pattern acquisition algorithm | is aligning sequences of tags |
| W06-2207 | algorithm with one iteration of the | pattern acquisition algorithm | . If one classifier converges |
| W06-2207 | patterns always improves if the | pattern acquisition algorithm | is " reinforced " with EM . For |
| W06-2207 | than the models generated by the | pattern acquisition algorithm | alone . When using the same pattern |
| H05-1076 | which differs from the answer | pattern acquisition algorithm | ) . E.g. , Question : " When |
| W06-2207 | The second learner is the actual | pattern acquisition algorithm | implemented as a bootstrapped |
| W06-2207 | Algorithm The lightly-supervised | pattern acquisition algorithm | iteratively learns domain-specific |
| W06-2207 | performance of the stand-alone | pattern acquisition algorithm | ( " boot - strapping " ) with |
| W06-2207 | ; ˆθ ) ( 2 ) 2.3 The | Pattern Acquisition Algorithm | The lightly-supervised pattern |
| W06-2207 | techniques ? Bootstrapping-based | pattern acquisition algorithms | can also be regarded as incremental |
