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As information increases explosively, the diversity and heterogeneity
of knowledge in different domains make it difficult to represent and
share knowledge. Meanwhile, the adaptive learning pattern is favored
by more and more learners, and how to acquire the knowledge in need
from complex knowledge bases and construct personal knowledge system
has recently become a hot spot of research.

Semantic learning web, which combines semantic web and web-based
education technologies, shed lights on the development of modem
education, and provide learners more efficient and high-quality
intelligent services. This paper, which based on semantic learning
web, semantically described domain knowledge and user pattern using
Ontology technology, presented the architecture of ontology-based
adaptive e-learning system (OntoAES) , provided the platform for
knowledge acquiring and sharing, and also provided learners with
effective learning services based on personal knowledge spaces and
preferences.

Firstly, various theory models of teaching and learning processes were
studied; the definition and description of learning behaviors in those
theory models were analyzed; based on different characteristics of the
learning behaviors, the features and requirements of the adaptive
e-learning process was studied in order to provide the theory
architecture and behavior model for the adaptive e-learning system;
how to present knowledge space was studied, domain knowledge model and
user knowledge space model were established.

Secondly, the features of domain knowledge was studied; as the
complexity and diversity of domain knowledge and the lack of ontology
engineering technology for domain experts make it difficult to develop
domain ontology, the method to establish ontology based on knowledge
engineering was proposed; the method to extract domain knowledge
concepts, define concepts hierarchical structure and construct the
relationship models were presented. The construction process to build
domain ontology was simplified.

Thirdly, computer science was choose as the research domain, based on
the domain knowledge space model, the knowledge taxonomy architecture
and concept sets were constructed, and domain knowledge ontology was
built. On the basis of E-learning standards, learning resources
description Ontology was established, which provided more semantics to
learning resources description model and more space to be expanded.

Fourthly, the user information model and user knowledge space model
were studied, the user model Ontology was built. The user information
sub-Ontology to describe user's basic information, the user preference
sub-Ontology to describe user's preference information, user
performance sub-Ontology to describe user's performance information
along with the user competency Ontology to describe user's learning
skills were established respectively. The semantic association among
user model ontology, domain knowledge ontology and learning resources
description Ontology was analyzed. A well-modeled basis was build for
the adaptive e-learning system.

Finally, the functional modules and system architecture of the
ontology-based adaptive e-learning system (OntoAES) were presented,
the correlation and application pattern between various Ontology and
system modules were studied. The adaptive e-learning steps and process
of the OntoAES were discussed. Based on analysis of user learning
behavior records, the analysis and definition of the potential
learning resource relation pattern based on users' use of log, the
relation model and user preference model were acquired through
information extraction and data mining technologies. Learning path
information in Domain knowledge and user preference information could
be refreshed; the model and method this paper presents were verified.

The main contributions are as follows:

1) Present the relation model of knowledge space, and method to build
domain knowledge Ontology based on knowledge engineering;
2) establish the Ontology of computer science domain and user model
Ontology, present the architecture of the Ontology-based adaptive
e-learning system;
3) Define the adaptive e-learning rules based on Ontology, build the
matching model between user preference ontology and study resource
description ontology, study resource relation model and preference
model based on data using.

This paper provides the basis and guidance for establishing the
ontology of the Education Semantic Web, and design and building of the
adaptive e-learning system. The future work includes the perfection of
the ontology and the function of the adaptive e-learning system, the
study of the matching model in ontology as well as the rules of
adaptive e-learning based on ontology, and to provide learners an
intelligent and efficient learning system.