Enhanced CAFÉ indexing algorithm using hashing function

The rapid growth of genomic databases and the increased of queries against those databases have lead to the needs of new and efficient search and compare techniques. Researcher in bioinformatics have concentrated on exploring into different approaches in order to solve the problem of cost associated with the exhaustive search techniques. One of these is the CAFE indexing algorithm which is considered to be a fast indexing algorithm in genomic information retrieval. However, there is still room for improvement in the CAFE indexing structure. This research aims to enhance the structure of CAFE inverted index by using a proper hash function to speedup retrieval process. The results of this research indicated that retrieval using the enhanced index is faster than retrieval using the original index (CAFÉ). The benefiot ratio of using the enhanced CAFE index compared to the retrieval time using the original CAFE index are between 62.8 to 74.9 for one query. However, we found that the memory space for storing the indexes are the same for both algorithms. The reason is that although the interval size decreases, each interval will now have an increased number of posting list.