@article{MAKHILLIJSC20149521225,
    title = {Encoded Temporal Database for ACS Classification Rule Discovery},
    journal = {International Journal of Soft Computing},
    volume = {9},
    number = {5},
    pages = {338-347},
    year = {2014},
    issn = {1816-9503},
    doi = {ijscomp.2014.338.347},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2014.338.347},
    author = {C.,S.,A. and},
    keywords = {Encoded database,ACS,KNN,temporal mining,time},
    abstract = {A temporal database which has time as the mandatory filed 
  is considered to make the system more practical and realistic. Memory utilization 
  is minimized by encoding the temporal database which involves several levels 
  of data based on time. The values in each level are used in the encoded database 
  to represent the transaction. This research proposes database encoding as a 
  new presentation which can reduce the size of database and improve the efficiency 
  of algorithms. An Encoded Temporal Database Method which identifies temporal 
  association rules from an item set that consists of transactions with their 
  corresponding valid time intervals. The application of Ant Colony Systems as 
  a classification rule discovery is explored and probably to perform a flexible 
  search over all possible logic combinations of the predicting attributes. The 
  encoding database is used in a Temporal Data Mining System rather than classification 
  rules in the sense of data mining. These results show to achieve both good predictive 
  accuracy and reduce number of rules at the same time.}
    }