IEEE Internet Computing
Automatic Fuzzy Ontology Generation for Semantic Web
IEEE Transactions on Knowledge and Data Engineering
A Learning Objects Recommendation Model based on the Preference and Ontological Approaches
ICALT '06 Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies
An ontology-based knowledge management system for flow and water quality modeling
Advances in Engineering Software
A methodology for constructing of philosophy ontology based on philosophical texts
Computer Standards & Interfaces
Automated ontology construction for unstructured text documents
Data & Knowledge Engineering
Knowledge Representation with Ontologies: The Present and Future
IEEE Intelligent Systems
A multilayer perceptron-based medical decision support system for heart disease diagnosis
Expert Systems with Applications: An International Journal
A genetic fuzzy agent using ontology model for meeting scheduling system
Information Sciences: an International Journal
Ontology-based concept similarity in Formal Concept Analysis
Information Sciences: an International Journal
Ontology development for unified traditional Chinese medical language system
Artificial Intelligence in Medicine
An approach for selecting seed URLs of focused crawler based on user-interest ontology
Applied Soft Computing
Editorial: A topic-specific crawling strategy based on semantics similarity
Data & Knowledge Engineering
Hi-index | 12.05 |
Among the developments of information technology, the most popular tools nowadays for seeking the knowledge are the Google or Yahoo keywords-based search engines on the Internet. Users can easily obtain the information they need, but they still have to read and organize those documents by themselves. Due to that reason, users have to spend most of time in browsing and skipping the documents they have searched. In order to facilitate this process, this paper proposes a query-based ontology knowledge acquisition system which dynamically constructs query-based partial ontology to provide proficient answers for users' queries. To construct the relationships and hierarchy of concepts in such an ontology, the formal concept analysis approach is adopted. After the ontology is built, the system can deduct the specific answer according to the relationships and hierarchy of ontology without asking users to read the whole document sets. We collected three kinds of sports news pages as source documents including those regarding NBA, CPBL and MLB to evaluate the precision of the system function in the experiment, which, as a result, reveals that the proposed approach indeed can work effectively.