Using data mining techniques to improve location based services

Abstract

With the rise of mobile technology in the recent years, a brand new form of service, Location Based Service (LBS), has emerged. Well performed and reliable LBS applications or services heavily rely on the accuracy and integrity of location data in addition to the timely update attributes. However, manually identifying and organizing the location information can be very time consuming and human error is another inevitable fact. Not many previous studies have been done concerning how to improve the accuracy and quality of location data through the data de-duplication process using web mining techniques. In this paper, we propose an efficient and cost-effective way to integrate the location information collected from multiple data sources and automate the de-duplication process with the help of data mining techniques. A series of experiments have been conducted to prove that the proposed approach can effectively and efficiently handle the location data integration tasks.

Location-Based Parallel Sequential Pattern Mining Algorithm

“…In recent years, with the advent of mobile technology, a new form of location-based service (LBS) has emerged. Many studies in the field of data mining are attempting to analyze data based on location [12], [13].…”