In this paper, we introduce a novel method based on context awareness, semantic similarities and customized weights for different categories to improve keyword matching. The algorithm is able to weight terms by using category information and semantic relationships with WordNet as a lexical database. To demonstrate the usefulness of the approach, several tests are run comparing against other existing methods such as Salton, Glasgow and Balanced Term Weighting schemes.