Research On Semantic Entity Recommendation Method Based On Fuzzy Mechanism

Decision-making goals are usually accompanied by multiple attributes and characteristics.When describing these attributes and characteristics,due to the different knowledge structures and levels of people,the quality of each attribute is sometimes difficult to accurately measure.However,fuzzy ontology description can just solve this dilemma.In the process of making recommendations for users,the recommendation system will face two problems.One is that there will be a lot of uncertain information in the recommended content which will contain both accuracy and ambiguity.So that the traditional fuzzy set theory cannot describe the semantic information in the recommended content knowledge well.The second is that the existing recommendation algorithm is difficult to deal with the problem of multiple score associations under a single entity.In response to the above problems,this thesis proposes a hesitation fuzzy operator and a new fuzzy operator distance measurement method that can be applied to criterion decisionmaking.On this basis,a semantic entity recommendation model based on a fuzzy mechanism is proposed,being applied in the recommended field of homestay hotels.First of all,a multi-criteria decision-making algorithm based on PHFAMM operator is proposed.In this part,combining MM operator and PHFN's Archimedean t-conorm and tnorm,Pythagoras hesitant fuzzy Archimedes MM(PHFAMM)operator and its weighted form are proposed.Besides a new method of MCDM based on PHFAMM is proposed.First,the generalized expression of the proposed operator is given,exploring and proving the properties of the operator.Then the four concrete expressions are constructed.On the basis of these specific expressions,a new method to solve the PHFN-based multi-criteria decisionmaking problem is developed.Finally,a set of experimental examples and qualitative and quantitative comparisons are used to verify the proposed multi-criteria decision-making method.Second,a new distance measurement algorithm based on PHFS is proposed.In this part,the five parameters of PFS namely membership degree,non-membership degree,uncertainty,and the strength and direction of membership degree are completely extended to the Pythagorean Hesitating Fuzzy Set(PHFS)to produce a new PHFS Distance measurement,applying the proposed method to the MCDM problem.First,the new PHFS distance metric is described.And its related properties and theorems are introduced.Then,by considering the distance between the positive ideal solution and each alternative,an MCDM method based on the new PHFS distance metric is proposed.Finally,practical experiments about the proposed method and comparative experiments with existing methods are introduced to verify the effectiveness and superiority of the proposed method.