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This paper fuses the techniques such as semantic network, the individuality service and agent, and references various research achievements of semantics Web on knowledge expression, RDF data manipulation and semantic retrieval, to propose an information retrieval model by combination of semantic with keyword based on
conquered, such as the knowledge comprehension capability. Thus, the precision and the recall were both pledged. The greenhouse domain ontology was set up, by the combination of semantic retrieval and keyword retrieval, farmers can communicate with expert directly. The disadvantage of lacking instructional expert was solved
This article presents an ontology-based approach to designing and developing new representation IR system instead of conventional keyword-based approach. Such representation improves the precision and recall of document retrieval. Experiments carried out on the ontology-based approach and keyword-based approach
competitors, track the developed trend of the industrial technique and improve the independent innovation capability and core competitiveness of their own. But at present patent information retrieval systems based on the keyword match can't satisfy the users' demands on accuracy and completeness. So, this paper proposes to
XBRL is a language for the electronic communication of business and financial data. XBRL has been extended to a dozen countries and regions. With XBRL data growing exponentially, XBRL database retrieval has become the urgent problem. Using traditional keyword matching method to query XBRL data is not efficient. In
information retrieval. Ontology-based information retrieval is different from the traditional keyword search. Semantic retrieval can be realized because Ontology knowledge base strengthens the intrinsic link of the concepts and the implied and unclear information can be deduced through logical reasoning. Our results show that
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