Task: Question Answering
Input (English): We compare our approach with several methods BIBREF1 , BIBREF31 , BIBREF11 , BIBREF8 , BIBREF10 , BIBREF39 in two cross-domain settings. Using string kernels, Giménez-Pérez et al. BIBREF10 reported better performance than SST BIBREF31 and KE-Meta BIBREF11 in the multi-source domain setting. In addition, we compare our approach with SFA BIBREF1 , CORAL BIBREF8 and TR-TrAdaBoost BIBREF39 in the single-source setting. Transductive string kernels. We present a simple and straightforward approach to produce a transductive similarity measure suitable for strings. Our transductive kernel classifier (TKC) approach is composed of two learning iterations.  
 Question: What machine learning algorithms are used?
Output (English): string kernels SST KE-Meta SFA CORAL TR-TrAdaBoost Transductive string kernels transductive kernel classifier