| P13-1137 | similarity . From each cluster , | multiple-sequence alignment | techniques are employed to capture |
| W02-1022 | This section describes general | multiple-sequence alignment | ; we discuss its application |
| W06-1603 | Lee ( 2003 ) proposed to apply | multiple-sequence alignment | ( MSA ) for tradi - tional , |
| J10-3003 | into a slotted lattice using a | multiple-sequence alignment | ( MSA ) algorithm . Compare all |
| J10-3003 | of an algorithm that computes a | multiple-sequence alignment | ( MSA ) for a cluster of sentences |
| P08-1116 | Barzilay and Lee ( 2003 ) applied | multiple-sequence alignment | ( MSA ) to parallel news sentences |
| W07-1429 | knowledge-lean algorithm that uses | multiple-sequence alignment | to learn generate sentence-level |
| P13-1137 | patterns among the abstracts , | Multiple-Sequence Alignment | ( MSA ) is first computed for |
| P13-1137 | domain-independent fashion . We apply | Multiple-Sequence Alignment | to induce abstract generation |
| W02-1022 | as a whole . Our work applies | multiple-sequence alignment | techniques to the mapping-dictionary |
| P14-1094 | one by 6.8 % for the problem of | multiple-sequence alignment | . 2 Related Work In the areas |
| N03-1003 | An Unsupervised Approach Using | Multiple-Sequence Alignment | </title> Barzilay Abstract We |
| N03-1003 | , similarities em - phasized . | multiple-sequence alignment | to clusters of sentences describing |
| W02-1022 | n-row correspondence table , or | multiple-sequence alignment | ( MSA ) . ( We explain how the |
| W02-1022 | three arguments of show-from . 2 | Multiple-sequence alignment | This section describes general |
| W02-1022 | Bootstrapping Lexical Choice via | Multiple-Sequence Alignment | </title> Regina Lillian Abstract |
| N03-1003 | paraphrasing . Our approach applies | multiple-sequence alignment | to sentences gathered from unannotated |
| W02-1022 | dictionaries in the next section . A | multiple-sequence alignment | algorithm takes as input n strings |
| W02-1022 | verbalizations , as computed by our | multiple-sequence alignment | method , exhibits high structural |
| W15-0617 | statistical machine translation or | multiple-sequence alignment | to extract paraphrase pairs from |
