Poster presentation from the Living the Future 7 Conference, April 30-May 3, 2008, University of Arizona Libraries, Tucson, AZ. / The University of Arizona Libraries implemented free in-house article delivery for the entire campus in August 2006. The success of collaborating with other universities and teams in the library resulted in making the Express Document service a premiere service for our faculty, staff and students. Learn about what we did and how we did it-our connections with Greater Western Library Alliance consortial partners for benchmarking this type of service, how we created a business plan, what steps were taken to implement the service, the technology purchased and implemented, our collaboration with other teams in the library, and how we measured our progress.

published_or_final_version / Computer Science and Information Systems / Doctoral / Doctor of Philosophy

The global network is changing the way every business works. In particular, new networked applications will affect the way in which organizations work with documents. Document management solutions help organizations run smarter and maximize business performance. This document management software was created to help people control and organize all of their work-related documents regardless of whether they exist as an email, a paper copy, a word processing document, an image, or a spreadsheet.

As XML gains popularity as the standard data representation model, there is a need to store, retrieve and update XML data efficiently. McXml is a native XML database system that has been developed at McGill University and represents XML data as trees. McXML supports both read-only queries and six different kinds of update operations. To support concurrent access to documents in the McXML database, we propose a concurrency control protocol called LockX which applies locking to the nodes in the XML tree. LockX maximizes concurrency by considering the semantics of McXML's read and write operations in its design. We evaluate the performance of LockX as we vary factors such as the structure of the XML document and the proportion of read operations in transactions. We also evaluate LockX's performance on the XMark benchmark [16] after extending it with suitable update operations [13]. Finally, we compare LockX's performance with two snapshot-based concurrency control protocols (SnaX, OptiX) that provide a committed snapshot of the data for client operations.

Traditional clustering methods, where documents are represented by term frequency vectors, are not very suitable for Lithuanian document clustering as there is no any freely available morphological analyzer or stemmer to make compact term dictionaries. It is still possible though to cluster Lithuanian documents using loose term dictionaries, but as Lithuanian is a highly synthetic language significant increase in resources and possibly inaccurate or distorted results must be taken into account. In this master thesis a clustering method for personally classified documents is deve­loped to overcome shortcomings of traditional document clustering stated above. In a new method documents are represented by tag frequency vectors, pair-wise similarities are measured by cosine coefficient and clustering itself is performed using experimentally selected bisecting K‑means algorithm. Experiments comparing developed method with traditional document clustering using loose term dictionary showed that former copes better with large document collections and/or large cluster number. At the same time subjective clustering estimation showed that even when new method demonstrates larger entropy and lower purity values, it still overcomes traditional method by clustering sense.

Given a set of peers with overlapping interests where each peer wishes to keep track of new documents that are relevant to their interests, we propose Shrack-a self-organizing peer-to-peer (P2P) system for document sharing and tracking. The goal of a document-tracking system is to disseminate new documents as they are published. We present a framework of Shrack and propose a gossip-like pull-only information dissemination protocol. We explore and develop mechanisms to enable a self-organizing network, based on common interest of document sets among peers. Shrack peers collaboratively share new documents of interest with other peers. Interests of peers are modeled using relevant document sets and are represented as peer profiles. There is no explicit pro file exchange between peers and no global information available. We describe how peers create their user pro files, discover the existence of other peers, locally learn about interest of other peers, and finally form a self-organizing overlay network of peers with common interests. Unlike most existing P2P file sharing systems which serve their users by finding relevant documents based on an instant query, Shrack is designed to help users that have long-term interests to keep track of relevant documents that are newly available in the system. The framework can be used as an infrastructure for any kind of documents and data, but in this thesis, we focus on research publications. We built an event-driven simulation to evaluate the performance and behaviour of Shrack. We model simulated users associated with peers after a subset of authors in the ACM digital library metadata collection. The experimental results demonstrate that the Shrack dissemination protocol is scalable as the network size increases. In addition, self-organizing overlay networks, where connections between peers are based on common interests as captured by their associated document sets, can help improve the relevance of documents received by peers in terms of F-score over random peer networks. Moreover, the resulting self-organizing networks have the characteristics of social networks.

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The Bleek and Lloyd Collection contains notebooks that document the tradition, language and culture of the Bushman people who lived in South Africa in the late 19th century. Transcriptions of these notebooks would allow for the provision of services such as text-based search and text-to-speech. However, these notebooks are currently only available in the form of digital scans and the manual creation of transcriptions is a costly and time-consuming process. Thus, automatic methods could serve as an alternative approach to creating transcriptions of the text in the notebooks. In order to evaluate the use of automatic methods, a corpus of Bushman texts and their associated transcriptions was created. The creation of this corpus involved: the development of a custom method for encoding the Bushman script, which contains complex diacritics; the creation of a tool for creating and transcribing the texts in the notebooks; and the running of a series of workshops in which the tool was used to create the corpus. The corpus was used to evaluate the use of various techniques for automatically transcribing the texts in the corpus in order to determine which approaches were best suited to the complex Bushman script. These techniques included the use of Support Vector Machines, Artificial Neural Networks and Hidden Markov Models as machine learning algorithms, which were coupled with different descriptive features. The effect of the texts used for training the machine learning algorithms was also investigated as well as the use of a statistical language model. It was found that, for Bushman word recognition, the use of a Support Vector Machine with Histograms of Oriented Gradient features resulted in the best performance and, for Bushman text line recognition, Marti & Bunke features resulted in the best performance when used with Hidden Markov Models. The automatic transcription of the Bushman texts proved to be difficult and the performance of the different recognition systems was largely affected by the complexities of the Bushman script. It was also found that, besides having an influence on determining which techniques may be the most appropriate for automatic handwriting recognition, the texts used in a automatic handwriting recognition system also play a large role in determining whether or not automatic recognition should be attempted at all.

The purpose of this thesis was to develop the best practices for completing a comparative analysis for a cultural landscape World Heritage nomination document. The research focused on existing secondary documents including written reports and nomination documents, as well as experts’ opinions. The two objectives of the research were to complete an examination of the existing World Heritage literature and to establish the best practices to undertake the comparative analysis. A comparative analysis is required to provide comparisons of the nominated site with sites that are on the World Heritage List and those that are not. The material emphasis of the World Heritage Committee review process is challenging for associative cultural landscape nominations. The individuality of each landscape and associated culture is what makes traditional sites unique and challenging to compare to other global sites.

No description available.