Generated rules for AIDS and e-learning classifier using rough set approach

The emergence and growth of internet usage has accumulated an extensive amount of data. These data contain a wealth of undiscovered valuable information and problems of incomplete data set may lead to observation error. This research explored a technique to analyze data that transforms meaningless data to meaningful information. The work focused on Rough Set (RS) to deal with incomplete data and rules derivation. Rules with high and low left-hand-side (LHS) support value generated by RS were used as query statements to form a cluster of data. The model was tested on AIDS blog data set consisting of 146 bloggers and E-Learning@UTM (EL) log data set comprising 23105 URLs. 5-fold and 10-fold cross validation were used to split the data. Naïve algorithm and Boolean algorithm as discretization techniques and Johnson’s algorithm (Johnson) and Genetic algorithm (GA) as reduction techniques were employed to compare the results. 5-fold cross validation tended to suit AIDS data well while 10-fold cross validation was the best for EL data set. Johnson and GA yielded the same number of rules for both data sets. These findings are significant as evidence in terms of accuracy that was achieved using the proposed mode

Generated rules for AIDS and e-learning classifier using rough set approach

The emergence and growth of internet usage has accumulated an extensive amount of data. These data contain a wealth of undiscovered valuable information and problems of incomplete data set may lead to observation error. This research explored a technique to analyze data that transforms meaningless data to meaningful information. The work focused on Rough Set (RS) to deal with incomplete data and rules derivation. Rules with high and low left-hand-side (LHS) support value generated by RS were used as query statements to form a cluster of data. The model was tested on AIDS blog data set consisting of 146 bloggers and E-Learning@UTM (EL) log data set comprising 23105 URLs. 5-fold and 10-fold cross validation were used to split the data. Naïve algorithm and Boolean algorithm as discretization techniques and Johnson’s algorithm (Johnson) and Genetic algorithm (GA) as reduction techniques were employed to compare the results. 5-fold cross validation tended to suit AIDS data well while 10-fold cross validation was the best for EL data set. Johnson and GA yielded the same number of rules for both data sets. These findings are significant as evidence in terms of accuracy that was achieved using the proposed mode

How to accelerate your internet : a practical guide to bandwidth management and optimisation using open source software

xiii, 298 p. : ill. ; 24 cm.Libro ElectrónicoAccess to sufficient Internet bandwidth enables worldwide electronic collaboration, access to informational resources, rapid and effective communication, and grants membership to a global community. Therefore, bandwidth is probably the single most critical resource at the disposal of a modern organisation. The goal of this book is to provide practical information on how to gain the largest possible benefit from your connection to the Internet. By applying the monitoring and optimisation techniques discussed here, the effectiveness of your network can be significantly improved

Cacheability study for web content delivery

Master'sMASTER OF SCIENC

Meaningless to Meaningful Web Log Data for Generation of Web Pre-caching Decision Rules Using Rough Set

Abstract—Web caching and pre-fetching are vital technologies that can increase the speed of Web loading processes. Since speed and memory are crucial aspects in enhancing the performance of mobile applications and websites, a better technique for Web loading process should be investigated. The weaknesses of the conventional Web caching policy include meaningless information and uncertainty of knowledge representation in Web logs data from the proxy cache to mobile-client. The organisation and learning task of the knowledge-processing for Web logs data require explicit representation to deal with uncertainties. This is due to the exponential growth of rules for finding a suitable knowledge representation from the proxy cache to the mobileclient. Consequently, Rough Set is chosen in this research to generate Web pre-caching decision rules to ensure the meaningless Web log data can be changed to meaningful information. Keywords-component; decision rules; rough set; web caching; web pre-fetching; web log data I

Reconstructing the Boundary of a Web Document

Documents found on the World Wide Web (WWW) may be composed of a single web page, or several web pages that are linked together by a table of contents or some other commonly known document construct. When a document spans multiple web pages, it is often inconvenient to print or download the entire document using available tools. This thesis introduces a concept called the document boundary to facilitate representation and analysis of multi-page web documents, and suggests a two-phase approach towards automated identification of document boundaries. In the first phase, individual pages are examined to determine which links are most likely to represent an intra-document link. This procedure is applied recursively to identify a group of candidate pages which may be part of the same document. In the second phase, the link topology and other features of the identified pages are examined in aggregate for indications of a multi-page document. A test suite of both single- and multi-page web documents was assembled using a mixture of handpicked documents and documents which were gathered by an arbitrary third party. The document boundary detection system was applied to the main page of each document. The document boundary detection system was able to achieve a success rate of 73% when its results were compared to the ground truth documents

The global intelligent file system framework.

"Since its inception the Internet has grown rapidly in both size and importance in our everyday lives. The Internet today is the preliminary model of what is commonly called the global information infrastructure. However, at the moment this "infrastructure" is considered to be an addition to our computer, and is not an integrated part of a file system which is essentially a "local information infrastructure" of a computer. Advancements in the sizes of disks in computers, network bandwidth and the types of media available mean users now keep large amounts of files in their personal data storage spaces, with little or no additional support for the organisation, searching or sharing of this data. The hierarchical model of file system storage is no longer the most effective way of organising and categorising files and information. Relying largely on the user, rather than the computer, being efficient and organised its inflexible nature renders it unsuitable for the meaningful coordination of an increasing bulk of divergent file types that users deal with on a daily basis. The work presented in this thesis describes a new paradigm for file storage, management and retrieval. Providing globally integrated document emplacement and administration, the GIFS (Global Intelligent File System) framework offers the necessary architecture for transparently directing the storage, access, sharing, manipulation, and security of files across interconnected computers. To address the discrepancy between user actions and computer actions, GIFS provides each user with a "Virtual Secretary" to reduce the cognitive workload and remove the time-consuming task of information organisation from the user. The Secretary is supported by a knowledge base and a collection of intelligent agents, which are programs that manage and process the data collected, and work behind the scenes aiding gradual proliferation of knowledge. The Virtual Secretary is responsible for providing fast and accurate assistance to aid users who wish to create, store, retrieve, share, secure and collaborate on their files. Through both system prototyping and performance simulation it is demonstrated that it is desirable as well as feasible to deploy a knowledge base in supporting an intelligent user interface that acts like a human assistant who handles paperwork, looks after filing, security and so on. This work provides the contribution of a new framework and architecture to the field of files systems and document management as well as focusing on reducing the burden placed upon users through everyday usage of computer systems. Such a framework has the potential to be evolved into a highly intelligent assistant to a user over a period of service and the introduction of additional agents, and provides the basis for advancements in file system and organisational technologies.