KNOWLEDGE REPRESENTATION IN THE RECOMMENDATION SYSTEM BASED ON THE WHITE BOX PRINCIPLE
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Abstract
The subject matter of the article is the construction of a rating list of goods and services in recommendation systems. The goal is to develop a knowledge representation model in recommendation systems using the white box principle. Such a model contains knowledge about the possible sequences of choosing restrictions on the properties of goods and services according to user preferences. The recommender system should provide a reasonable choice of the object according to the requirements of the user, subject to restrictions on the key properties of this object. Tasks: to structure the process of applying the principles of black and white boxes when building recommendations based on the use of a knowledge base; develop knowledge representations according to the principle of the white box in order to combine a static description of the properties of objects and a description of possible sequences for clarifying the requirements for the properties of these objects. The principles used are: the principle of the white box, which provides an account of requirements that take into account the properties of the constituent elements of the object selected by the consumer. The following results are obtained. The key features of the processes of forming recommendations on the principles of black and white boxes based on the use of the knowledge base are highlighted. The knowledge representation is developed according to the principle of the white box, which allows taking into account both the properties of objects and the process of their selection by the consumer. Conclusions. The scientific novelty of the results is as follows. A model for representing knowledge in a recommendation system according to the principle of a white box is proposed. The declarative aspect of this representation of knowledge is implemented in the form of predicates that define restrictions on the values of the properties of objects offered to the consumer. The procedural aspect is implemented in the form of adapted temporal dependencies that specify the sequence of refinement of time limits. This model combines the advantages of approaches based on the similarity of customer requirements and the similarity of product characteristics, which makes it possible to adjust recommendations online for a cold start situation. With this adjustment, it is advisable to use the similarity of the user selection processes for given requirements for goods.
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