Dissertation > Excellent graduate degree dissertation topics show

A Support Vector Machine and Transformation-based Error Driven Learning Method for Biological Entity Recognition

Author: HuangHaoZuo
Tutor: WangTing
School: National University of Defense Science and Technology
Course: Computer Science and Technology
Keywords: Information Extraction Named Entity Recognition Biological entity recognition Support Vector Machine Error - driven learning method based on conversion Generalization capability
Type: Master's thesis
Year: 2008
Downloads: 56
Quote: 1
Read: Download Dissertation


Based statistical machine learning method and rule-based method combined and applied to the field of biological entity recognition , the use of a typical representative of the SVM statistical learning theory as a concrete realization of machine learning methods , and the use of conversion - based error-driven learning method SVM test results obtained amendments to improve the precision and recall rate of biological entity recognition . This article first by extracting more rich feature set , such as word features , context features , part of speech characteristics , characteristics of the word form the core word feature and stop word characteristics , use the training corpus released by JNLPBA SVM classifier training , and then use the training the SVM model after the announcement of the test corpus JNLPBA identification of biological entities . Training corpus and test corpus statistics based statistical machine learning methods applied to biological entities to identify areas of the existence of some problems , such as learning generalization ability , feature selection problems , the introduction of external resources issues and data uneven , and so on . To further improve the effect of identifying the experimental use of error - driven learning method based on the conversion of the results of SVM annotation correction , transformation rules better linguistic phenomena in biology text mining , to further improve the accuracy of SVM method and Zhao back rate . By the method used in comparison with other researchers , this paper has achieved considerable results with a lot of mature applications .

Related Dissertations

  1. Research on Automatic Detection Algorithm for Substructure Distress of Highway Pavement Based on SVM,U418.6
  2. Research on Domain Entity Attribute and Event Extraction Technology,TP391.1
  3. Research on Transductive Support Vector Machine and Its Application in Image Retrieval,TP391.41
  4. Research on Temporal Information Recognition and Normalization,TP391.1
  5. Fault Diagnosis Method Based on Support Vector Machine,TP18
  6. Study on Growth Monitoring Technique Based on Pixel Un-Mixing Method and HJ Remote Sensing Images in Paddy Rice,S511
  7. Research for Infrared Image Target Identification and Tracking Technology,TP391.41
  8. Research of Diagnosing Cucumber Diseases Based on Hyperspectral Imaging,S436.421
  9. Active faults based radar image information extraction method applied research and demonstration,P542.3
  10. Based on high-resolution remote sensing data mining houses information extraction,TP751
  11. Research on Intrusion Detection Based on Feature Selection,TP393.08
  12. Research of Fault Diagnosis Method of Analog Circuit Based on Improved Support Vector Machines,TN710
  13. Study on Data Extraction and Semantic Annotation for Specific Field Deep Web,TP311.13
  14. Chinese study nested entity recognition method named,TP391.1
  15. Research on Classification and Matching for Hand Vein Image,TP391.41
  16. Optimizzation on Tread Rubber Loss Factor Based on Support Vector Machine,U463.341
  17. Research on Feature Extraction, Selection and Classification Algorithms for Pulmonary CAD,TP391.41
  18. The Research for Named Entity Recognition and Relation Extraction in Text,TP391.1
  19. Time-varying Outage Model and Fault Diagnosis of Oil Immersed Transformers Based on DGA,TM411
  20. Eutrophication Prediction Based on ANN and SVM for Xiangxi Bay of the Three Gorges Reservoir,X832
  21. Ontology-based medicine named entity recognition technology research,TP391.1

CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory
© 2012 www.DissertationTopic.Net  Mobile