Abstract: In this paper, we revisit our approach to construction of semantic-linguistic Feature
Vectors (FVs) used in search. These FVs are built based on domain semantics encoded in an
ontology and enhanced by relevant terminology from Web documents. The contributions of this
paper are the evaluation of constructed FVs and the analysis of their impact on search
performance. This completes the validation of the proposed approach concluding that the
proposed metrics provide good indications of the quality of the FVs. Yet, the results suggest the
metrics need to be revised to fit the needs of search applications.