No abstract

The problem of constructing and expanding the temporal knowledge base for the information-control system is considered. This knowledge base is formally represented by the Markov logic network. It is shown that the behavior of the control object of a given class can be reflected in the form of a set of weighted temporal rules. These rules are formed on the basis of identifying links between events that reflect known variants of the behavior of the control object. A method is proposed for calculating the weights of temporal rules in a Markov logic network for a given level of detail of the control object. The level of detail is determined by the context for executing the sequences of control actions and for weighted temporal rules is specified by selecting subsets of the event attributes. The method includes such basic phases: preparation of a subset of temporal rules for a given level of detail; finding the weights of the rules taking into account the a priori probabilities of the event traces. The method creates conditions for supporting management decisions in information management systems at various levels of detail of complex management objects. Decision support is provided by predicting the probability of success in executing a sequence of actions that implement the management function in the current situation. These probabilities are determined using the weights of the temporal rules.

The problem of shilling attacks detecting in e-commerce systems is considered. The purpose of such attacks is to artificially change the rating of individual goods or services by users in order to increase their sales. A method for detecting shilling attacks based on a comparison of weighted temporal rules for the processes of selecting objects with explicit and implicit feedback from users is proposed. Implicit dependencies are specified through the purchase of goods and services. Explicit feedback is formed through the ratings of these products. The temporal rules are used to describe hidden relationships between the choices of user groups at two consecutive time intervals. The method includes the construction of temporal rules for explicit and implicit feedback, their comparison, as well as the formation of an ordered subset of temporal rules that capture potential shilling attacks. The method imposes restrictions on the input data on sales and ratings, which must be ordered by time or have timestamps. This method can be used in combination with other approaches to detecting shilling attacks. Integration of approaches allows to refine and supplement the existing attack patterns, taking into account the latest changes in user priorities.

The problem of constructing and using the knowledge representation in the process control system is studied. It is shown that when implementing knowledge-intensive business process management, it is necessary to use automated construction and expansion knowledge base to support decision-making in accordance with the current state of the context for the implementation of business process actions. The state of the context is specified as a set of weighted logical facts, the arguments of which are the values of the attributes of the events of the business process log. The sequence of the process implementation at each moment of time is displayed in the form of a probabilistic distribution of the possible rules of executing the actions of the business process in this context. The method of automated construction and updating of the knowledge base of the information system of process control is proposed. The method includes the stages of forming knowledge representation templates, constructing context descriptions, logical facts, constructing rules, and calculating the probability distribution for rules. The method creates opportunities to support decision-making on the management of the business process in the event of a discrepancy between the current implementation of the business process and its model.