In this paper, we introduce a new type of queries, keyword-matched skyline queries, that retrieve tuples which are not dominated by any other tuples and whose text description matches with the given query keywords. Since conventional skyline processing methods do not handle keyword matching, skyline query processing would be necessary on the keyword-matched tuples computed from n-tuples with textual information. However, this combination approach incurs a significant processing overhead. In this paper, we propose an efficient algorithm for keyword-matched skyline queries. Our proposed algorithm makes use of $IR^2$-Tree as the index structure and branch and bound search to traverse the tree. Therefore, our proposed algorithm can prune unqualified nodes during traversing the tree. We carried out extensive experiments with various parameters and data sets. The results of the experiments show our proposed algorithm is very efficient with regard to computational cost and I/O cost.