Dissertation > Excellent graduate degree dissertation topics show

Research on Data Graph Retrieval Algorithm Based on Bayesian Network

Author: ZhengShiJun
Tutor: ShiYiMin
School: Dalian Maritime University
Course: Computer Science and Technology
Keywords: Bayesian Network Subgraph Search Uncertain Data Graph Object Graph
CLC: TP391.41
Type: Master's thesis
Year: 2013
Downloads: 29
Quote: 0
Read: Download Dissertation

Abstract


Data graph is a pattern which is constituted by a number of given points and lines connecting two points. With the points representing things and the lines representing corresponding relationship between two things, this pattern is usually used to describe a certain specific relationship among things. A number of query methods were proposed which were aimed at the deterministic data graph. However, there are still a lot of uncertainty information. To solve this problem, some scholars introduced probabilistic theory into the uncertain data graph, this provides a new method for querying and processing uncertain data graph, but the probability value is uncertain in some cases. For example, a disease induced by the probability of another disease, in the case of constant external conditions, this probability value is determined, but when the condition changes, this probability value can only be used as a reference.Bayesian network is a retrieval method works under the given model and rules, which has a unique advantage in the uncertainty reasoning. Due to the uncertainty of the data in disease areas, the traditional Bayesian network retrieval model can not meet the user’s search request Based on the study of traditional Bayesian network retrieval model, the Bayesian network data graph retrieval model is proposed which includes resource network and query network.The application of Bayesian network in uncertainty reasoning is introduced into data graph retrieval in order to solve the uncertainty problem encountered in the data graph retrieval, and an object graph method based on the conditional probability table is proposed.A global reasoning is needed when retrieved by Bayesian network, this practice requires a lot of time although it improves the precision rate. Since Bayesian network need much time, it has a disadvantage in the retrieval efficiency. Therefore, an effective subgraph retrieval algorithm is proposed in this thesis Bayesian method just acts as an aid in data graph retrieval. Reasoning will be done only when the indirect neighbor conditional probability is absent in this thesis, data graph structure information is still through efficient data retrieval algorithms to find out. On this basis, this thesis implements the data graph retrieval prototype system based on the Bayesian network, and experimental results showed that the effective subgraph retrieval algorithm has better precision.

Related Dissertations

  1. Multi-Sensor Information Fusion and Its Applications on Wearable Computer,TP202
  2. Research and Implementation of the Gene Bayesian Network Construction Algorithm Based on Multi-core Environment,Q75
  3. Risk Analysis for the Rock of Tunnel Based on the Bayesian Network,U455.1
  4. An Expectation Maximization Application for Decision Tree Classifiers on Datasets with Missing Values,TP311.13
  5. Event Detection Modeling and Optimization in Intelligent Video Surveillance,TP391.41
  6. Analyzing the Factors of Rural Consumer Price Index by Bayesian Network,F323.8
  7. Research and Application of Quality Control Classification Based on Bayesian Network,TP18
  8. Research of the Petroleum Pipelines Corrosion Based on Bayesian Networks,TE988.2
  9. Decision-oriented influence diagram node aggregation method,N945.25
  10. Data Mining in TCM Medical Records Based on Bayesian Network,TP311.13
  11. Text Categorization Research Based on TAN Model,TP181
  12. Research on Thermal Error Modeling of Machine Tools Based on Bayesian Network,TG659
  13. The Research on Structure Learning of Dynamic Bayesian Network,TP183
  14. The Effect of Time Course Data Measurement on the Construction of Gene Regulation Network,Q78
  15. Bayesian network model HP large format printers marketing mix strategy,F416.4
  16. Research on Motor Fault Diagnosis Using Multi-Source Information Fusion Technology,TM307
  17. E-learning Learners’ Learning Style and the Design of Individualized Network Curriculum,G434
  18. The Model of Knowledge Cluster Based on Bayesian Network under Mass Behavior and Its Application,F224
  19. Research on Operators’ Situation Assessment Model in the Nuclear Power Plant,F426.23;F426.61
  20. Research on a Recommender System Based on Bayesian CBR,TP391.3
  21. Overhead Traveling Crane Metal Structure Allowable Stress Method Validation and Safety Assessment,TH215

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
© 2012 www.DissertationTopic.Net  Mobile