Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Data mining (2)
- Graph algorithms (2)
- Big data (1)
- Binary Classification (1)
- Branching processes (1)
-
- Canonical labelling (1)
- Cell-graph (1)
- Choice Theory (1)
- Cleft formation (1)
- Clinical Language Understanding (1)
- College students (1)
- Computational Modeling (1)
- Computer networks (1)
- Computers (1)
- Constructivist Theory of Education (1)
- Data Quality (1)
- Data integrity (1)
- Database (1)
- Decision Theory (1)
- Decision trees (1)
- Distributed algorithms (1)
- Distribution (1)
- Education (1)
- Educational technology (1)
- Entity Resolution (1)
- Frequent subgraph (1)
- GGH Model (1)
- Graph (1)
- Graph connectivity (1)
- Graph mining (1)
- Publication
- Publication Type
Articles 1 - 8 of 8
Full-Text Articles in Physical Sciences and Mathematics
Review Of Whatis.Com, Edited By Margaret Rouse And Ivy Wigmore, Et Al., Michael Knee
Review Of Whatis.Com, Edited By Margaret Rouse And Ivy Wigmore, Et Al., Michael Knee
University Libraries Faculty Scholarship
No abstract provided.
Effective Entity Resolution Methodology For Improving Data Quality And Reliability Of Service-Oriented Applications, Ewa Musial
Legacy Theses & Dissertations (2009 - 2024)
This dissertation proposes new paradigms for improving the testing, reliability of service-oriented applications as well as the quality of data. Since it is difficult to track information flowing through the multiple tiers of an application, testing service-oriented systems can be very challenging. We present a methodology for testing service-oriented applications that takes into account all the components, including services, external services, and data components. The results of our experiments demonstrate that this approach greatly improves the effectiveness of testing service-oriented applications.
Computational Modeling-Driven Study Of Signaling Pathway Affecting Cleft Formation During Submandibular Salivary Gland Development, Shayoni Ray
Legacy Theses & Dissertations (2009 - 2024)
Branching morphogenesis is a conserved mechanism of mammalian organ development (salivary glands, lungs, mammary glands, pancreas, kidney, etc.), and has been a classic topic of study for generations of developmental biologists. During the process of tissue formation, several cellular and molecular and protein signaling events occur at successive stages enabling proper formation of tissue shape and structure. In order to provide a comprehensive understanding of the process of branching morphogenesis, we need a systems level approach to integrate multifactorial information. My overall global hypothesis is that multiple mathematical modeling approaches can be utilized to extract crucial cellular and tissue level …
Graph Mining And Module Detection In Protein-Protein Interaction Networks, Ru Shen
Graph Mining And Module Detection In Protein-Protein Interaction Networks, Ru Shen
Legacy Theses & Dissertations (2009 - 2024)
Graphs are intuitive representations of relational data. Graphs have been widely used to represent biological molecular networks that operate in the living systems. In the study of systems biology, using graph mining techniques and graph-theory-based algorithms to
Time Will Tell : Temporal Reasoning In Clinical Narratives And Beyond, Weiyi Sun
Time Will Tell : Temporal Reasoning In Clinical Narratives And Beyond, Weiyi Sun
Legacy Theses & Dissertations (2009 - 2024)
Temporal reasoning in natural language refers to the extraction and understanding of time-related information conveyed in free text. A clinical narrative temporal reasoning component can enable a spectrum of medical natural language processing (NLP) applications that directly improve patient care documentation efficiency, accessibility and accountability. This dissertation contributes in three subtasks under temporal reasoning: temporal annotation, temporal expression extraction and temporal relation inferences. The temporal annotation work described in the dissertation produced one of the first publicly available clinical narratives. We published one of the first sets of temporal
Roughened Random Forests For Binary Classification, Kuangnan Xiong
Roughened Random Forests For Binary Classification, Kuangnan Xiong
Legacy Theses & Dissertations (2009 - 2024)
Binary classification plays an important role in many decision-making processes. Random forests can build a strong ensemble classifier by combining weaker classification trees that are de-correlated. The strength and correlation among individual classification trees are the key factors that contribute to the ensemble performance of random forests. We propose roughened random forests, a new set of tools which show further improvement over random forests in binary classification. Roughened random forests modify the original dataset for each classification tree and further reduce the correlation among individual classification trees. This data modification process is composed of artificially imposing missing data that are …
Exploratory Study Of Student Instructional Choice In Online Learning, Andrew Hurd
Exploratory Study Of Student Instructional Choice In Online Learning, Andrew Hurd
Legacy Theses & Dissertations (2009 - 2024)
This exploratory study considers choice theory, decision theory, and the constructivist theory of education to explore college-level computer science learners' behavior when presented with multiple instructional modes (instructional methods for the presentation of course content, such as video, text, audio, animation, etc.) in an online learning environment.
A Query-Oriented Approach To Graph Series Distribution And Replication : Dissertation, Alan G. Labouseur
A Query-Oriented Approach To Graph Series Distribution And Replication : Dissertation, Alan G. Labouseur
Legacy Theses & Dissertations (2009 - 2024)
Most real-world networks evolve over time. We are surrounded by them: social networks, citation networks, transportation networks, the Web, and more.These evolving, dynamic networks can be modeled as series of graphs (graph snapshots) that represent those networks at different points in time. While many single-graph systems are available today, they lack support for efficiently managing series of large graph snapshots. Our G* system enables efficient storage and querying of these graph snapshots by taking advantage of their commonalities.