Experimental research work on query recommendations that aims to speed user search on electronic documents is presented in this paper. The authors developed a new online analytical processing (OLAP) algorithm based on the frequency and association of selected keywords.

Three methods--a single match method, a distance method, and a correlation method--were created to grade the validity of a set of keywords. The authors compared the OLAP algorithm to the well-known Apriori algorithm. The results show that the OLAP algorithm is more stable. In addition, sampling with a few iterations can reach high accuracy levels.

While the paper has a good motivation, it lacks a more extended presentation of the work and the results are not well discussed or justified.