P13-1170 from answer candidates to the answer re-ranking . The features used in our previous
P06-1112 in Table 1 . However , removing answer re-ranking does n't affect much . Since
D12-1034 al. , 2007 ) . The second step , answer re-ranking , is the focus of this work .
P07-1098 passages from them . A further answer re-ranking phase is optionally applied .
P06-1135 validating answer to QTi . Algorithm A. Answer re-ranking using constraints validation
P13-1170 regarded as answer candidates in the answer re-ranking . See Murata et al. ( 2007 )
P07-1098 classification of questions and answers and answer re-ranking . We define ( a ) new tree structures
J11-2003 evaluate many linguistic features for answer re-ranking . Although several of these features
D12-1034 composed of answer retrieval and answer re-ranking . The first step , answer retrieval
P07-1098 on question classification and answer re-ranking for Web-based QA systems . In
P13-2075 minimum Bayes risk ( MBR ) based Answer Re-ranking ( MBRAR ) approaches for the
P13-1170 answer candidate extraction and answer re-ranking ( Fig. 1 ) . This architecture
P07-1098 different sentence predicates . 4.3 Answer re-ranking The output of the answer classifier
P13-1170 al. ( 2007 ) for more details . Answer re-ranking : Re-ranking the answer candidates
P07-1098 between questions and answers in answer re-ranking , to our knowledge no study uses
P07-1098 classification , answer classification and answer re-ranking . We have defined tree structures
P07-1098 Semantic Tree Kernel . In the answer re-ranking task , we approach the problem
D12-1034 Set1 ) . It shows the effect of answer re-ranking when evaluating our proposed
P06-1112 to ( Cui et al. , 2004 ) . 3 . Answer Re-ranking ( Section 5 ) . We disable this
P07-1098 for question classification and answer re-ranking . We define new tree representations
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