Extended Dynamic Logic Programs And Application In Product Presonalized Recommendation

Currently, the answer set programming has become an important knowledgerepresentation and reasoning tool in the field of artificial intelligence. It is adescriptive framework for problem solving which is very suitable for modeling andautomatic solution commonsense reasoning problems. Dynamic logic programming isan important form of answer set programming.Alferes et al proposed dynamic logic programming. Dynamic logic programmingcan deal with the knowledge base update well, but it can not describe and process theknowledge base update with preferences. Therefore, in this paper, on the basis of thedynamic logic programming, we propose a new extension of dynamic logicprogramming language, and give the optimal answer set semantics. In order todescribe and handle knowledge base update with preferences problem, this paperpresents a new dynamic logic programming through the head of the rules usingordered disjunction. This new program language has richer syntax. At the same time,it enhances the knowledge description and reasoning ability, expands range ofapplications, but does not increase its computational complexity. Meanwhile, we givean example about the movie personalized recommendation to illustrate the applicationof the new language in the product information personalized recommendation.This paper which describes the product information personalizedrecommendation is mainly to resolve the problem of user demand constraints. Butbecause of the lack of domain knowledge of users or the variability of user needs,they may appear unreasonable needs, so that the program will not be able to give areasonable recommended solution. To solve this problem, this paper proposes aweighted quantitative information personalized recommendation solution of theoptimization method. The method can solve the problem which in the case of users’unreasonable needs by weighting users’ needs rules and give a solution which meetusers’ needs best.