A Grid-Enabled Infrastructure for Resource Sharing, E-Learning, Searching and Distributed Repository Among Universities

In the recent years, service-based approaches for sharing of data among repositories and online learning are rising to prominence because of their potential to meet the requirements in the area of high performance computing. Developing education based grid services and assuring high availability reliability and scalability are demanding in web service architectures. On the other hand, grid computing provides flexibility towards aggregating distributed CPU, memory, storage, data and supports large number of distributed resource sharing to provide the full potential for education like applications to share the knowledge that can be attainable on any single system. However, the literature shows that the potential of grid resources for educational purposes is not being utilized yet. In this paper, an education based grid framework architecture that provides promising platform to support sharing of geographically dispersed learning content among universities is developed. It allows students, faculty and researchers to share and gain knowledge in their area of interest by using e-learning, searching and distributed repository services among universities from anywhere, anytime. Globus toolkit 5.2.5 (GTK) software is used as grid middleware that provides resource access, discovery and management, data movement, security, and so forth. Furthermore, this work uses the OGSA-DAI that provides database access and operations. The resulting infrastructure enables users to discover education services and interact with them using the grid portal

Research Enterprise Office Search Portal

All the employees in University Technology Petronas need to access information instantaneously in order to enhance their functionality and efficacy. Is it easy to collaborate and gather the right information at the right time? Is all the research within a company documented? Is it easily available to all employees? And what happens when an employee leaves the company? This project is an analysis of current practices and outcomes of the search portal and the nature of it as they are evolving in most of the organizations. The findings suggest that interest in search engines across a variety of industries is very high, the technological foundations are varied, and the major concerns revolve around achieving the correct amount and type of accurate research and garnering support for contributing to the search portal. Implications for practice and suggestions for future research are drawn from the study findings. This project focused on the search function. The research is on how to make this search portal useful to the University Technology Petronas (UTP) community that is the UTP staff and lecturers. These search portal solutions are ideal for operations and maintenance manuals that once were reserved for 3-inch thick binders sitting on the shelves of many treatment plants. Moving the manual standard procedures, troubleshooting, theory, alarms, and equipment descriptions to an electronic, web-based solution offers many benefits. For one, the information can be updated and kept current much more effectively because it can be changed in one place and instantly updated at all access points. By developing this search portal, the staff and lecturers will be able to get information fast and efficiently

Identifying experts and authoritative documents in social bookmarking systems

Social bookmarking systems allow people to create pointers to Web resources in a shared, Web-based environment. These services allow users to add free-text labels, or “tags”, to their bookmarks as a way to organize resources for later recall. Ease-of-use, low cognitive barriers, and a lack of controlled vocabulary have allowed social bookmaking systems to grow exponentially over time. However, these same characteristics also raise concerns. Tags lack the formality of traditional classificatory metadata and suffer from the same vocabulary problems as full-text search engines. It is unclear how many valuable resources are untagged or tagged with noisy, irrelevant tags. With few restrictions to entry, annotation spamming adds noise to public social bookmarking systems. Furthermore, many algorithms for discovering semantic relations among tags do not scale to the Web. Recognizing these problems, we develop a novel graph-based Expert and Authoritative Resource Location (EARL) algorithm to find the most authoritative documents and expert users on a given topic in a social bookmarking system. In EARL’s first phase, we reduce noise in a Delicious dataset by isolating a smaller sub-network of “candidate experts”, users whose tagging behavior shows potential domain and classification expertise. In the second phase, a HITS-based graph analysis is performed on the candidate experts’ data to rank the top experts and authoritative documents by topic. To identify topics of interest in Delicious, we develop a distributed method to find subsets of frequently co-occurring tags shared by many candidate experts. We evaluated EARL’s ability to locate authoritative resources and domain experts in Delicious by conducting two independent experiments. The first experiment relies on human judges’ n-point scale ratings of resources suggested by three graph-based algorithms and Google. The second experiment evaluated the proposed approach’s ability to identify classification expertise through human judges’ n-point scale ratings of classification terms versus expert-generated data

Internet search techniques: using word count, links and directory structure as internet search tools

A thesis submitted for the degree of Doctor of Philosophy ofthe University of LutonAs the Web grows in size it becomes increasingly important that ways are developed to maximise the efficiency of the search process and index its contents with minimal human intervention. An evaluation is undertaken of current popular search engines which use a centralised index approach. Using a number of search terms and metrics that measure similarity between sets of results, it was found that there is very little commonality between the outcome of the same search performed using different search engines. A semi-automated system for searching the web is presented, the Internet Search Agent (ISA), this employs a method for indexing based upon the idea of "fingerprint types". These fingerprint types are based upon the text and links contained in the web pages being indexed. Three examples of fingerprint type are developed, the first concentrating upon the textual content of the indexed files, the other two augment this with the use of links to and from these files. By looking at the results returned as a search progresses in terms of numbers and measures of content of results for effort expended, comparisons can be made between the three fingerprint types. The ISA model allows the searcher to be presented with results in context and potentially allows for distributed searching to be implemented