An Efficient Algorithm for Mining Fuzzy Temporal Data

Mining patterns from fuzzy temporal data is an important data mining problem. One of these mining task is to find locally frequent sets, In most of the earlier works fuzziness was considered in the time attribute of the datasets .Although a couple of works have been done in dealing with such data, little has been done on the implementation side. In this article, we propose an efficient implementation of an algorithm for extracting locally frequent item sets from fuzzy temporal datasets. Our implementation is a Trie-based (Prefix-tree) implementation. The efficacy of the method is established with an experiment conducted on a synthetic dataset. KeywordsTemporal dataset, Fuzzy temporal dataset. Frequent item set, Locally frequent item set, Core of a fuzzy number, Data mining, Fuzzy membership function, -cut of a fuzzy number.