ИНТЕЛЛЕКТУАЛЬНАЯ РЕКОМЕНДАТЕЛЬНАЯ СИСТЕМА ДЛЯ ПРОСТРАНСТВЕННОГО АНАЛИЗА

Abstract

The work is devoted to the analysis of mechanisms of formation of recommendations andevaluation of the user's reaction to them in the interactive mode of work with the geoinformationsystem. One of the important areas of application of recommender systems is the search and decision-making in spatial situations. A peculiarity of this class of problems is the uncertainty of taskdefinition and ambiguity of decision evaluation. Users are often faced with problems that do nothave a clear formulation. To try to solve them, it is necessary not only to designate the direction ofsolution search, but also to find an adequate sequence of tasks with clearly formulated input andoutput data. Recommendations in such cases are designed in a dialogue with the user-analyst todevelop a strategy for finding solutions. In this paper we study a smart recommendation systemusing the experience of dialog interaction. We propose a model of adaptation to the mental imageof the problem, which builds the user, taking into account the levels of situational awareness andcognitive load. The peculiarity of the model is the use of visual cartographic objects, which areindicators of the state of the mental image. A recommendation is represented by a set of objectsthat are introduced into the field of cartographic analysis. This implicitly induces a certain semanticdirection of increasing situational awareness. A criterion of satisfaction with the recommendationis suggested. A diagram of recommender system states, which describes the selection of context,adequate to the problem being solved, is given. The context is understood as an informationobject, capable of providing program functions and data for solving problems of a limited class.A sequence of contexts in an analysis session is considered as a precedent of experience. Indicatorsof trend, tendency and rhythm are proposed for possible chains of contexts. The degree ofsemantic proximity of precedents to the current course of search for a solution is estimated bythese indicators. Their use will increase the speed of adaptation.