Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  address the problem of ansring b ontology queries efficiently. An ontology is formalized as a deductive ontology base (DOB), a deductive database that comprises the ontology's inference axioms and facts. A cost-based query optimization technique for DOB is presented. A hybrid cost model is proposed to estimate the cost and cardinality of basic and inferred facts. Cardinality and cost of inferred facts are estimated using an adaptive sampling technique, while techniques of traditional relational cost models are used for estimating the cost of basic facts and conjunctive ontology queries. Finally,  implement a dynamic-programming optimization algorithm to identify query evaluation plans that minimize the number of intermediate inferred facts.  modeled a subset of the b ontology language Lite as a DOB and performed an experimental study to analyze the predictive capacity of our cost model and the benefits of the query optimization technique. Our study has been conducted over synthetic and real-world b ontology language ontologies and shows that the techniques are accurate and improve query performance.
['Edna Ruckhaus', 'Eduardo Ruiz', 'Maria-Esther Vidal']
I am writing a research paper on a idea Query evaluation and optimization in the semantic web
[{"from": "human", "value": "I am writing a research paper on a idea Query evaluation and optimization in the semantic web"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  address the problem of ansring b ontology queries efficiently. An ontology is formalized as a deductive ontology base (DOB), a deductive database that comprises the ontology's inference axioms and facts. A cost-based query optimization technique for DOB is presented. A hybrid cost model is proposed to estimate the cost and cardinality of basic and inferred facts. Cardinality and cost of inferred facts are estimated using an adaptive sampling technique, while techniques of traditional relational cost models are used for estimating the cost of basic facts and conjunctive ontology queries. Finally,  implement a dynamic-programming optimization algorithm to identify query evaluation plans that minimize the number of intermediate inferred facts.  modeled a subset of the b ontology language Lite as a DOB and performed an experimental study to analyze the predictive capacity of our cost model and the benefits of the query optimization technique. Our study has been conducted over synthetic and real-world b ontology language ontologies and shows that the techniques are accurate and improve query performance."}]