Mining and Clustering of Location Based Services on Basis of Moving Transactions
In today’s world everything is fast paced and internet as become necessity of life we need it at every step. With the invention of smart phone GPS enabled cell user can ask for any service via Information service and Application provider from anywhere any time. This business model is known as moving commerce .It provides Location based services through moving phone. One of the active topics in mining is the mining and prediction of moving movements and associated transactions. Most of existing studies focus on discovering moving patterns from the whole logs. The issue with this method is that it does not provide accurate information as it depends on spatial clustering where as Location based services require non spatial clustering. The other issue with it is that most methods requires user to set the parameters which is highly impossible in an active environment. Moreover in moving environment the user profiles are seldom known but what we know is the moving transaction patterns. In the paper we will use an algorithm, namely, Temporal Moving Sequential Pattern Mine based on clustering, to discover the Cluster-based Temporal Moving Sequential Patterns .User clusters are constructed by a algorithm named Cluster- Object-based Smart Cluster Affinity Search Technique similarities between users are evaluated by the proposed measure, Location-Based Service Alignment (LBS-Alignment).In the algorithm is also proposed to use time as also one of the dimensions where similar moving characteristics exist.