PLI-X: Temporal Association Rules Mining in Customer Relationship Management Systems

The temporal association rules mining has recently become an important technology in the field of the Customer Relationship Management (CRM), which can be useful for improving the customer enterprise relationship. Also, the dynamic nature of the CRM systems is made necessity of using efficient and rapid algorithms in order to extract valid patterns in this field. Hence, this paper proposes an efficient algorithm of incremental mining for temporal association rules in CRM entitled PLI-X. The four significant features that are considered for this algorithm are:(1) generating  valid temporal association rules after adding the new transactions to the database, (2) performing algorithm on the whole temporal database instead of a small section of it, (3) performing the temporal transactional databases of the non-numeric, and (4) quickly generating the temporal association rules and reducing the run time by partitioning the candidate itemsets based on the previous partitions and scanning database when scan is necessary. Experimental result is the valid proof for the correctnessof this assertion. It seems that the PLI-X algorithm can be used as a strong tool in order to extract valid patterns and discover useful temporal association rules in the field of CRM.

Keywords:

Temporal Database , CRM , Incremental Mining , Pre-large Itemsets