The flexible architecture we have presented enables interesting future research : ( i ) a straightforward improvement is the use of lexical similarity to reduce data sparseness , e.g. ( Basili et al. , 2005 ; Basili et al. , 2006 ; Bloehdorn et al. , 2006 ) .
effective use of wordnet semantics via kernelbased learning
Roberto Basili Marco Cammisa Alessandro Moschitti
It is possible that this could be improved with a better strategy for representing dependency structure for tree kernels , or if the tree kernels could be incorporated into the structural learning framework . The flexible architecture we have presented enables interesting future research : ( i ) a straightforward improvement is the use of lexical similarity to reduce data sparseness , e.g. ( Basili et al. , 2005 ; Basili et al. , 2006 ; Bloehdorn et al. , 2006 ) . However , the similarity between subjective words , which have multiple senses against other words may negatively impact the system accuracy .
The flexible architecture we have presented enables interesting future research : ( i ) a straightforward improvement is the use of lexical similarity to reduce data sparseness , e.g. ( @@CITATION ; Basili et al. , 2006 ; Bloehdorn et al. , 2006 ) .