New prediction model for pre-fetching in mobile database

Abstract

In mobile environment, pre-fetching method is used to prevent network congestion, delays and latency problems and to improve data availability during disconnection. Many pre-fetching strategies have been introduced. Lately, the pre-fetching techniques in mobile systems become more complicated in which to support new types of applications such as in wireless environments. Due to this complication, researchers start to introduce new technique where it requires data mining technique to improve the situation in involuntary disconnection. Previously, the data is filtered using an objective measurement where data are generated based on the structure of a query pattern and quantified using statistical methods. The measures are not good enough to solve the rule quality problems as in answering query in mobile environment. In this study, a new prediction model is proposed to generate data item for additional criterion before sending to mobile users. This new criterion of data is measured by a subjective measurement which is based on the subjectivity and the understandability of the users who examine the query patterns. Therefore, it is expected that mobile users can make use and access the data items that are beyond their expectation to proceed with their job further without any problem.

Integrated Measurement for Pre-Fetching in Mobile Environment

“…Lately, with the advancement of mobile computing technology the pre-fetching techniques in mobile systems become more complicated in which to support new types of applications such as in mobile environments (Shi et al, 2005, Darus and Ibrahim, 2010, Darus and Ibrahim, 2011. Due to this complication, researchers started to introduce new intelligent technique which requires data mining process (Yucel et al, 2000).…”