http://hdl.handle.net/1957/10238 Search the Channel search http://ir.library.oregonstate.edu/jspui/simple-search http://hdl.handle.net/1957/12426 Title: Indexing Web 2.0 Applications<br/><br/>Authors: Mohan, Sumana; Bose, Dr. Bella; Budd, Dr. Timothy; Minoura, Dr.Toshimi<br/><br/>Abstract: This project aims at implementing Indexing for Web 2.0 Applications. Ajax applications consist of a set of states which are generated by the user through actions such as click, focus, blur etc. events. By saving these DOM states we can index information obtained from dynamically generated web content. To prevent indexing of duplicate DOM states, a Tree Edit Distance algorithm known as Fast Match Edit Script has been implemented.For ranking the results, the ranking function tf-idf has been implemented. Wed, 19 Aug 2009 13:04:16 GMT http://hdl.handle.net/1957/11770 Title: Load testing of loan search project report<br/><br/>Authors: Pai, Jiten Wed, 03 Jun 2009 18:14:29 GMT http://hdl.handle.net/1957/10151 Title: Myopic policies for budgeted optimization with constrained experiments<br/><br/>Authors: Lin, Wei; Fern, Alan; Fern, Xiaoli<br/><br/>Abstract: Motivated by a real-world problem, we study a novel setting for budgeted optimization where the goal is to optimize an unknown function f(x) given a budget. In our setting, it is not practical to request samples of f(x) at precise input values due to the formidable cost of experimental setup at precise values. Rather, we may request constrained experiments, which give the experimenter constraints on x for which they must return f(x). Importantly, as the constraints become looser, the experimental cost decreases, but the uncertainty about the location of the next observation increases. Our problem is to manage this trade-off by selecting a sequence of constrained experiments to best optimize f within the budget. We propose a number of myopic policies for selecting constrained experiments using both model-free and model-based approaches, inspired by policies for unconstrained settings. Experiments on synthetic and real-world functions indicate that our policies outperform random selection, that the model-based policies are superior to model-free ones, and give insights into which policies are preferable overall.<br/><br/>Description: Graduation date: 2008 Tue, 20 Jan 2009 16:20:42 GMT http://hdl.handle.net/1957/9984 Title: PHP cloud computing platform<br/><br/>Authors: Kalyan, Arvind<br/><br/>Abstract: Motivation for cloud computing applications are listed. A Cloud Computing framework –MapReduce – is implemented. A document indexing application is built as an exampleMapReduce application on this framework. Focus is given to ease of job submission andscalability of the underlying network.<br/><br/>Description: Graduation date: 2009 Tue, 30 Dec 2008 21:04:54 GMT