Browsing by Author "Barker, Kenneth E."
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Item Open Access A data mining framework for efficient discovery of classification rules(2004) Gopalan, Janaki; Barker, Kenneth E.Associative classification is an important research topic in data mining (DM). The thesis proposes a framework to derive accurate and interesting classification rules using the association rule mining (ARM) technique. To effectively address the rule discovery task, in the framework, two fundamental problems in the pre-processing and the post-processing components of the DM process are identified. In the preprocessing component, it is identified that the choice of the training set is an important factor in deriving good classification rules. The thesis proposes a novel technique using a genetic algorithm (GA) to find an appropriate split of a dataset into training and test sets. Using the obtained training set as the input to the ARM technique generates high accuracy classification rules. It is also identified that an algorithm (or heuristic) is required to find the best set of interesting and accurate rules from the discovered ones. In the post-processing component, the thesis proposes a pruning strategy using a GA to find the accurate interesting rules.Item Open Access A lattice-based privacy aware access control model(2012) Ghazinour Naini, Kambiz; Barker, Kenneth E.Privacy is a leading concern for individuals who utilize computing resources for a variety of reasons, such as shopping online or visiting their health care provider. As service providers are collecting more data from customers, it becomes more crucial to the data providers how their data is treated after being collected. Hence, the fundamental part of this thesis is about data privacy. There are several ways proposed in the literature to preserve the privacy of data one of them is using access control models. Conventional access control models are not suitable for privacy preserving uses and a new model should be designed based on the characteristics of privacy predicates. One important aspect that is not sufficiently addressed by the research community is to consider the privacy preferences of data providers as well as the practices of collectors. Hence, in the new privacy aware access control there is a mechanism to give the opportunity to the data providers to express their privacy preferences about how the provided data is used.Item Open Access Alternate 3d control-display mappings(2007) Keijser, Jeroen; Carpendale, Sheelagh; Barker, Kenneth E.Item Open Access Bounding volumes in 3-dimensional r-trees(2010) Nielson, Jordan; Barker, Kenneth E.Item Open Access Conversion from relational schema to XML nested-based schema(2003) Duta, Angela Cristina; Barker, Kenneth E.Item Open Access Data management in publish/subscribe and data broadcast systems(2009) Omotayo, Adesola Morayo; Barker, Kenneth E.Item Open Access Delegation of access rights in a privacy preserving access control model(2011) Moniruzzaman, Md.; Barker, Kenneth E.Item Open Access Fragmenting XML documents in distributed XML database systems(2003) Chen, Ying Qi; Barker, Kenneth E.Item Open Access Geospatial information extraction from the web for gis: process, algorithms, and framework(2011) Shi, George; Barker, Kenneth E.Item Open Access Hybrid cache invalidation schemes in mobile computing environments(2006) Bao, Yuliang; Barker, Kenneth E.Item Open Access Immersive and interactive visualization of volume interiors with a flashlight-based detail-in-context lens tool(2007) Stromer, Julie; Sensen, Christoph W.; Barker, Kenneth E.Item Open Access Inference protection through query translation(2005) Yu, Bo; Barker, Kenneth E.Item Open Access Methodology to minimize cost and time for new data warehouse implementations(2004) Lam, Stephen; Barker, Kenneth E.A data warehouse's many different components make setting one up a non-trivial and expensive task (R.K. 98). This thesis describes a new light-weight data warehouse implementation methodology that minimizes cost and production time while ensuring the core requirements of a typical data warehouse system are included. The methodology enables fast initial development with scalable architecture for future growth. From a maintenance perspective, the methodology minimizes the ongoing data refresh cost. This is important because data refresh cost is the major maintenance cost in a typical data warehouse system. The data quality is also improved by using the methodology. The above advantages are due to the small team structure, single database architecture, metadata approach, data modeling approach, Extract Transformation and Loading (ETL) approach, tools selection and web portal presented in the methodology.Item Open Access MOP: mining opinion from customer reviews(2009) Xu, Hong; Barker, Kenneth E.Item Embargo New approaches to vertical partitioning(2003) Du, Jun; Barker, Kenneth E.Item Open Access P4A: a new privacy model for XML(2009) Duta, Angela Cristina; Barker, Kenneth E.Item Open Access Prisql: a privacy preserving sql language(2010) Pun, Sampson; Barker, Kenneth E.Item Open Access Privacy-based retention(2010) Wu, Leanne; Barker, Kenneth E.Item Open Access Reduced-parameter approaches to time-sensitive discovery and analysis of navigational patterns(2006) Udechukwu, Ajumobi Okwuchukwu; Barker, Kenneth E.Navigational pattern discovery is the application of pattern mmmg techniques to navigational studies. Previous work on navigational pattern discovery strongly relies on user-specified preset parameters (notably, support thresholds). A major drawback of parameter-driven data mining is setting appropriate thresholds. In most practical scenanos, data mining 1s iterative, meaning that the analyst may mme at varymg thresholds before arriving at satisfactory results. This usually proves expensive m parameter-driven techniques. These challenges faced in parameter-driven data mining become very pronounced in environments with continuously streaming data where it is no longer possible to apply simple iterative data mining techniques. This thesis explores a new design goal for the discovery and analysis of navigational patterns, which aims to reduce the use of pre-defined parameters required at the beginning of the mining process (reduced-parameter mining), and completely removes pre-defined parameters wherever possible (parameter-free mining). The new paradigm is developed in the context of time-sensitive navigational pattern discovery. Three broad dimensions are explored where time can significantly affect the ways navigational patterns are to be discovered or analyzed. The first dimension 1s m information systems where the content continuously changes with time (thus affecting navigational behaviour). The second dimension is in high-volume information systems, where the usage-logs continuously change with time. The final dimension of temporal significance in navigational pattern discovery explored in the thesis is the representation and analysis of navigational patterns as full temporal objects ( or time series). This thesis conceptualizes the notions of time significance in navigational pattern discovery with respect to the dimensions identified above, and then proposes novel techniques for discovering navigational patterns in such environments that are based on reduced-parameter or parameter-free principles. Interestingly, the results from this thesis show that reduced-parameter mining and parameter-free mining are practical concepts. The results also show that reduced-parameter/parameter-free mining techniques outperform parameter-based mining techniques in environments that require continuous updates of patterns. This is contrary to the general belief that early introduction of predefined parameters always improves the mining process. This result has strong implications to other data mining tasks.Item Open Access Replica placement and selection strategies in data grids(2007) Rahman, Mohammad Rashedur; Barker, Kenneth E.