TABLE OF CONTENTS We implemented the proposed approximation and indexing techniques as they are described in the previous sections and here we present experimental results evaluating our techniques. We describe the datasets and then we continue by presenting the results. The purpose of our experiments is twofold: first, to evaluate the efficiency and accuracy of the approximation algorithm presented in Section 4 and second to evaluate the indexing technique that we discussed in the previous section. Our experiments were run on a PC Pentium III at 1 GHz with 128 MB RAM and 60 GB hard disk.
Here we present the results of some experiments using the approximation algorithm to compute the similarity function S2. Our dataset here comes from marine mammals' satellite tracking data [2]. It consists of sequences of geographic locations of various marine animals (dolphins, sea lions, whales, etc) tracked over different periods of time, that range from one to three months ( SEALS dataset). The length of the sequences is close to 100.
In Table 1 we show the computed similarity between a pair of sequences in the SEALS dataset. We run the exact and the approximate algorithm for different values of ? and ? and we report here some indicative results. K is the number of times the approximate algorithm invokes the LCSS procedure (that is, the number of translations c that we try). As we can see using only a...
