Intelligent file hoarding for mobile computers
MobiCom '95 Proceedings of the 1st annual international conference on Mobile computing and networking
Automated hoarding for mobile computers
Proceedings of the sixteenth ACM symposium on Operating systems principles
Profit Mining: From Patterns to Actions
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Association Rules for Supporting Hoarding in Mobile Computing Environments
RIDE '00 Proceedings of the 10th International Workshop on Research Issues in Data Engineering
Mining Optimal Actions for Profitable CRM
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Hoarding and prefetching for mobile databases
ICIS-COMSAR '06 Proceedings of the 5th IEEE/ACIS International Conference on Computer and Information Science and 1st IEEE/ACIS International Workshop on Component-Based Software Engineering,Software Architecture and Reuse
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
Association based prefetching algorithm in mobile environments
ICESS'04 Proceedings of the First international conference on Embedded Software and Systems
Information-Based pruning for interesting association rule mining in the item response dataset
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
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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.