Dissertation > Excellent graduate degree dissertation topics show
Research on Named Entity Recognition Based on Rules
Author: ZhouKun
Tutor: HuXueGang
School: Hefei University of Technology
Course: Computer Software and Theory
Keywords: Chinese information processing Named Entity Recognition Chinese word segmentation Noumenon
CLC: TP391.1
Type: Master's thesis
Year: 2010
Downloads: 161
Quote: 2
Read: Download Dissertation
Abstract
|
Chinese word segmentation is the first step in natural language processing . In practical applications , segmentation constrained by many factors , unknown words segmentation is one of the important factors to influence the segmentation correct rate . The main form of unknown words , including place names , organization names named entity . Therefore, the identification of named entities fusion to Chinese word segmentation process plays an important role to improve the accuracy of Chinese word . In addition , the study named entity recognition , information extraction , information retrieval , machine translation , text classification applications achieve has important theoretical and practical value . This article 's main research contents are as follows : (1) propose a fusion named entity recognition of Chinese sub- word model , word segmentation process at the same time carry out identification of named entities , reducing the named entities, etc. are not logged word of recognition errors and cause the Chinese lexical segmentation errors, thus improving the accuracy of the segmentation . (2) hierarchical classification system , based ontology building the knowledge base of Chinese names , Chinese names field of knowledge is divided into several levels , low levels of the field of knowledge is the basis of the high-level , high-level domain knowledge is the low level of generalization and summarization , effectively improve the names Knowledge Base maintainability . ( 3 ) build a rule base named entity recognition , using the rule - matching method to identify named entities . Recognition system has self-learning ability , while identifying named entities recognition results can be analyzed to generate to feedback new rules to the rule base , has a good effect of named entity recognition .
|
Related Dissertations
- Applied Research of Ontology in Intelligent Residence Community,TP391.1
- Research and Implement of Chinese Word Segment Techniques Based on the Conditional Random Field,TP391.1
- The Research for Named Entity Recognition and Relation Extraction in Text,TP391.1
- Research on Approaches of the Subjective Automated Assessment,TP391.1
- Research on Semantic-based Inspection of Construction Engineering Quality,TP391.1
- Based WebHarvest the Chinese financial news search engine design and implementation,TP311.52
- Chinese XML Compression Technology,TP311.11
- Ontology-based medicine named entity recognition technology research,TP391.1
- CRF -based named joint extraction of entities and relationships,TP391.4
- Click data and search results based on fragments excavated named entities,TP391.3
- Corporate e-mail monitoring system design and implementation,TP393.098
- Research and Implementation of Semantic Search System in Printer Operation Based on Ontology,TP391.1
- Research and Implementation of Knowledge Organization and Retrieval Based on Ontology,TP391.1
- Study on Extraction and Storage of OWL Ontology Based on Relational Database,TP391.1
- Chinese named entity recognition and disambiguation of,TP391.1
- Intelligent Analysis and Implement of Compliant Information Based on Filter Technology,TP391.1
- Probability and statistics based on dictionaries and Chinese word segmentation algorithm,TP391.1
- Ontology Based Approach to Fine-Granularity Knowledge Management,TP391.1
- Research on Information Retrieval Technology Based on Semantic Web,TP391.3
- Study on Chinese Text Classification Combined with Ontology,TP391.1
- Research and Implementation of Learning Computer Organization Principle Based on Course Ontology,TP391.1
CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Text Processing
© 2012 www.DissertationTopic.Net Mobile
|