Browsing by Subject "Database searching"
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Item Active learning and compilation of higher order schema integration queries(2005) Barbanson, François Gérard; Miranker, Daniel P.After nearly 30 years, database integration remains the province of engineers and application developers. In an informal proof, Krishnamurthy, Litwin and Kent [KLK91] demonstrated that only higher order relational languages such as SchemaSQL and SchemaLog [LSS96] are general enough to concisely describe the merging of data from multiple heterogeneous sources. However, those languages are incrementally harder to program than SQL. A modern solution is to provide a GUI language with the same capabilities. However, a Query-by-Example (QBE) [Zloof77] type interface does not allow the unambiguous specification of higher order data integrating queries. We propose an architecture comprising three layers. In the middle layer, the user expresses the desired federated view through a QBE inspired user interface. Further learning proceeds via a sample selection method asking the user to validate examples of federated records. This interaction ends when the system is satisfied it has converged to the exact view definition the user intends. The bottom layer provides the execution mechanism for higher order data manipulations by compiling higher order relational definitions into first-order SQL programs. The top layer component of the architecture assists the learning algorithm by collecting meta-data and catalog statistics. Our primary contributions comprise a taxonomy examining trade-offs between complexity and completeness and identifying various classes of higher order relational data manipulations. The architecture delimits three separate challenges, which must be overcome in order to propose a solution. Our compilation for SchemaSQL proposes novel theoretical complexity guarantees. Type-based vertical partitioning of the meta- data ensures that the result can be properly optimized by existing SQL engines. Sample selection constraints specific to databases require the introduction of a third kind of instance label in the training set of our learner. We derive a new algorithm by modifying Mitchell’s version spaces [Mitchell82] in order to handle this new kind of label. We prove that the modified algorithm preserves the original properties of version spaces and avoids the possibility of deadlock. We introduce a sample selection heuristic that converts catalog statistics into a classic inductive bias. Finally, we develop the Sphinx prototype, carry out experiments and demonstrate the system on an application.Item Relational database applications' optimization and performance study(Texas Tech University, 1998-08) Thiruvaipati, PrashanthThe objective of the thesis is to develop efficient query processing techniques for large relational database applications since, when such applications have to process more than a million records, performance becomes a key issue. Some techniques rely upon massive hardware architectures and new database software to improve efficiency of large database systems. One of the objectives of the thesis, however, is to develop optimization techniques using existing hardware and software. Performance improvement may be achieved by the use of parallel application processes that can process different fragments of a database at the same time. Further performance improvement is achieved by using dynamic SQL and simulating an SQL outer join in the 'C programming language. Simulating the SQL function MAX and proper locking mechanism resulted in marginal performance improvement. Database design to support the use of parallel application processes and the other techniques is presented. Applications are built to test the techniques and the performance results are presented and discussed. Multiple test cases are run for each technique to ensure that the results are similar in time. For each technique, the scenarios of maximum performance improvement, the underlying mechanism, and possible limitations are discussed.Item Structure of a firm's knowledge base and the effectiveness of technological search(2004) Yayavaram, Sai Krishna; Fredrickson, James W.; Ahuja, GautamThis dissertation examines the impact of coupling that exists between the knowledge elements of a firm (i.e., the structure of the firm’s knowledge base) on the firm’s technological search activity. I define coupling as the decision made on how the search across two knowledge elements should be combined and distinguish it from interdependence, which is the inherent relationship between these two elements. I ask two questions: 1) How does the structure of a firm’s knowledge base impact the usefulness of a firm’s inventions? 2) How does the prior structure of a firm’s knowledge base affect the malleability of the knowledge base? Malleability is defined as the capacity for adaptive change. Inventions are generated when existing knowledge elements are combined in novel ways. Given the large number of potential combinations of knowledge elements, the problem of searching for technological inventions is computationally intractable. I use the NK model to study this computationally complex problem and argue that the structure of a knowledge base can mitigate the negative effects of complexity. In the first part of the dissertation, I show through computer simulations that a structure that is nearly decomposable (i.e. high coupling within a cluster of elements along with low coupling across clusters) increases the effectiveness of search on an NK landscape. In the second part of the dissertation, I test the relationship between near decomposability in the structure of a knowledge base and technology search in the context of the worldwide semiconductor industry. I find support for the hypothesis that a nearly decomposable structure improves the search for technological inventions. Further, I also find support for the hypothesis that firms with a nearly decomposable structure are likely to undergo a larger change in their knowledge base over time.Item The applications of new information technology in a college library: a survey of microcomputer databases service at Texas Tech University Library(Texas Tech University, 1988-08) Liu, Young-yiNot available