Automated Teller Machines Location's Information Retrieval Search Engine Using Suffix Tree Clustering Technique

Abstract

In this paper, the researcher presented the Automated Teller Machines Location's Information Retrieval Search Engine using Suffix Tree Clustering Technique. This new offering is very helpful to the day to day evolving demands of money transactions of the bank customers, especially during unexpected Automated Teller Machines failures. With an application of Suffix Tree Clustering Technique, the proposed Automated Teller Machines Location Information Retrieval Search Engine is not only limited to produce more efficient, accurate and precise Automated Teller Machines location search results than the current bank existing system. It also provides easier access focused control in information dissemination to provides 24/7 access to the list of ATM location booth with the corresponding ATM information's according to the areas of familiarity of the bank customers. It's also conveying innovation to the bank online services to exploit the provisions of Online and Offline ATM status transparency to the bank customers and avoid the bank customers to other banks high transactions fees. This claim is reinforced by 100% average effectiveness of precision, recall and F-measure experimental results on bank ATM locations data set. In spite of the rapid growth of improving and modernizing the Automated Teller Machines services there is still a lot ideas in fetching new offerings to modified Automated Teller Machines Location's Information Retrieval Search Engine in the country to dig up more accessible ATM location with a timely manner as contribution to the fast-paced era of modernization and technology.