Research On Method Of Data Sources Selection And Constructing Domain Ontology

The research on ontology construction method is necessary for the widely ontology application,and plays a practical role and value in the conversion to the next generation of WWW.The current ontology construction research seldom focuses on the analysis of internal features in information source,but mostly on the process analysis of the method,so better application performance is difficult to achieve.Based on an intensive analysis of information source,this study propose a document decomposition model,an input-output model and a double vector space model,and these model integrate many intelligent methods,such as artificial neural networks and fuzzy formal concept analysis.Based on these results,manual and automatic construction methods are derived for ontology construction tools.The main research and results are as follows:(1) Information source is the kernel and critical for building domain ontology with regard to ontology quality and efficiency.Considerable progress has been achieved in this respect;yet, traditional method only takes the frequency or percentage of terms and concepts in the whole document into account,but do not take the location information into consideration,which leads to a low accuracy.Via an abstract method analysis,this paper constructs a document decomposition model and it firstly addresses the characteristics of information source,such as conception,relation and predictability;then,these characteristics weights are determined by the improved Vector Space Model(VSM),ontology relation distance and neural network respectively.Based on Java+Oracle technique,the study design and implement the information source selection system.By this system,the document weights are obtained by training a neural network with simulated data.Combined with a real document data set of "Wetland Protection",the model is tested and a good order effect on the document selection is attained.(2) Manual method for ontology construction in specific domain——Wetland protection domain ontology.The primal objective of the study is to build digitized wetland and realize knowledge management and information sharing.Wetland ontology is the basis to achieve this objective.The analysis result indicates that the current ontology techniques suffer from the many disadvantages,such as insufficiency demand,no planning,no formalization and ignorance of ontology sharing and reusing.To overcome these disadvantages,the study proposes the WP-Onto(Wetland Protection Ontology) Method.It begins with a demand analysis of wetland protection domain,followed by the building of an input-output driven model with an object of wetland resources.The method is then used to collect concepts and terms related to wetland protection,and generate respectively every knowledge set in the driven model;finally,it goes through refinement,extraction,and supplement before its establishment.Beside,the study also focuses on the application of wetland ontology,and it consists of information sharing and knowledge management.(3) Methodology of ontology building based on Web resources will not only shorten the constructive period of the ontology,but also extend the application field of the ontology.A lot of progress has been made,but there are still some difficulties,such as the web data extraction and knowledge acquisition.This paper focuses on the characteristics of ontology construction data,such as dynamics,largeness,variation and openness;the fundamental problem--formal representation method.This paper also concludes the key technique and difficulty of ontology construction.An initial system structure has been proposed,which provides a guideline for ontology construction based on web.(4) To build an efficient and accurate ontology learning tool,this paper proposed a double vector space model(DVSM) that developed from the classical single vector space model based on the object-oriented idea.The model has not only attribute characters but also strong relation characters.On the basis of this model,fuzzy formal concept analysis(FFCA) ontology learning technology is introduced because it considers the distributed property of data in the DVSM and is predominant to solve the problems about ontology continuity,ontology relationship obtainment,etC.An ontology learning tool has been implemented based on the method above, and it is a powerful support for automatic/semi-automatic ontology construction.In summary,the study presents several important research results on ontology construction: A method to build an ontology information source selection system based on the document decomposition model;A.manual ontology construction method——WP-Onto for wetland protection domain;An ontology learning tool based on the analysis of web data and combination of FFCA method.Based on the information source selection method,the study makes a useful investigation to manual and automatic ontology construction method,and the good results are obtained.