Research On Uncertain Semantic Temporal Query Middleware Based On Substructure Logic

The main purpose of the paper is to solve the dilemma optimization problem of temporal query and its computational complexity between expressive ability and computationalcomplexity.Underthecatalysisofapplicationssuchas spatio-temporal big data,spatio-temporal crowdsourcing and cloud computing,temporal formalization calculus has become increasingly complex,and the Category of knowledge expression has been greatly expanded.However,at the same time as the ability to express knowledge is improving,the computational complexity of the computational system has also escalated,and even combinatorial explosions.There are dilemma choices between computational complexity and expressiveness,if we reduce the ability to express and accelerate the speed of calculation,it will easily lead to lack of precision;if we reduce the computational complexity,it will make it difficult to express knowledge completely and cause errors in calculation and prediction.Especially in terms of uncertainty semantics,multi-valued and fuzzy semantics,there is an urgent need to optimize the computing capabilities and resources.The main method is the use of sub-structure logic supported by group theory and highly abstracted sub-structure logic as a formal tool to optimize temporal logic calculation and query middleware prototype design and implementation.The main research contents include:1)Establishing the mechanism of uncertainty semantic calculus based on substructure logic,mapping temporal attributes into type semantics,stripping time attributes from syntactic calculus,and simplifying syntactic logic;2)According to syntactic logic,put forward reliable Complementing the algebraic semantic model of syntactic calculus,it builds a faster and more efficient logical semantics than syntactic calculus and speeds up query operations.3)According to the calculus system,a query middleware prototype is designed and implemented,and the uncertain semantic temporal query is optimized.Corresponding theory is used to map the 13 kinds of temporal relations of the classical Allen method into the calculus system,and qualitatively proves that the calculation time complexity of the computation system and the middleware is only O(n).At the same time,according to the middleware prototype constructed in this thesis,the middleware prototype query accuracy verification experiment was carried out,including the accurate processing of uncertainty semantics,multivalued and fuzzy semantics,and the accurate calculation of the time interval relationship,taking into account the tense.Experiments were conducted on the complexity of the query time in this study,and quantitatively performed on four irregular natural data tables1000 times,including cross-comparison experiments of temporal queries and non-temporal queries(traditional queries).The experimental results show that the feedback result of the temporal query is exactly the same as the prediction result of the theory.The accuracy of the query of the temporal middleware prototype is 100%.The curvature of the query increases with the number of experiments without curvature,and it increases linearly.The time complexity is not.High-order arguments(such as n~2,etc.)appear,and the time complexity of completing the temporal query operation is only O(n).Qualitative and quantitative analysis shows that the proposed uncertainty semantic temporal calculus and its middleware prototype are efficient and reliable.The scope of processing covers all the temporal relationships,and has the commonality of calculation and optimization,providing theoretical and technical support for temporal information processing.