Search

Search Results

• MODIFIED WORD SENSE DISAMBIGUATION METHOD BASED ON DISTRIBUTED REPRESENTATION METHODS

  Y. A. Kravchenko, Mansour Ali Mahmoud, Mohammad Juman Hussain

  2021-08-11

  Abstract ▼

  In the text mining tasks, textual representation should be not only efficient but also interpretable,
  as this enables an understanding of the operational logic underlying the data mining
  models. This paper describes a modified Word Sense Disambiguation (WSD) method which extends
  two well-known variations of the Lesk WSD approach. Given a word and its context, Lesk
  bases its calculations on the overlap between the context of a word and each definition of its senses
  (gloss) in order to select the proper meaning. The main contribution of the proposed method is
  the adoption of the concept of “similarity” between definition and context instead of "overlap", in
  addition to expanding the definition with examples provided by WordNet for each sense of the
  target word. The proposed method is also characterized by the use of text similarity measurement
  functions defined in a distributed semantic space. The proposed method has been tested on five
  different benchmark datasets for words sense disambiguation tasks and compared with several
  basic methods, including simple Lesk, extended Lesk, WordNet 1st sense, Babelfy and UKB. The
  results show that proposed method outperforms most basic methods with the exception of Babelfy
  and the WN 1st sense methods.

• KNOWLEDGE FOR ARGUMENTATION IN COMPARISON OF SPATIAL SITUATIONS

  S.L. Belyakov, N.А. Golova, К.S. Yavorchuk, I. N. Rosenberg

  2022-05-26

  Abstract ▼

  The traditionally used way to assess the quality of the solution proposed by an intelligent
  system is to explain the course of logical inference. Knowledge about reasoning is used to argue
  the choice of a solution option. The sequence of applied rules, the facts used and the confirmed
  hypotheses are considered arguments that should convince the user of the validity of the formed
  conclusion. The disadvantage of this method of explanation is that it reflects a formally correct,
  but devoid of semantic content, course of reasoning. The argumentation of the solution obtained is
  based on the tracing protocol, which is essentially no different from debugging information when
  tracing programs. The argumentation in this case is far from the meaning of the situation. The
  meaning is understood as a given set of transformations of the situation that preserve the immutability
  of its perception by a human analyst. Knowledge about the semantic content of situations
  should be presented in a special fashion. In this paper, we consider a representation containing a
  precent and its permissible transformations. In this form, spatial situations in geoinformation systems
  are described. For argumentation, it is proposed to use special relations between images of
  situations. The concept of the area of applicability of the image is introduced. The mutual arrangement of the spatial-temporal and semantic shell of images and the areas of their applicability
  is considered as a carrier of the relationship. Information about relationships is extracted from the
  structure of the cartographic database. The relations of inheritance, aggregation, composition,
  generalization and association of classes of objects are considered. Knowledge for argumentation
  is provided by the rules for determining the reliability index of expert conclusion for individual
  relationships and their combinations. A method of automatic rule generation is proposed.
  The relations for comparison of levels of reliability of rules are given.

• INTELLIGENT RECOMMENDER SYSTEM FOR SPATIAL ANALYSIS

  S.L. Belyakov, А.V. Bozhenyuk, N.А. Golova, К.S. Yavorchuk, I.N. Rosenberg

  14-26

  2025-07-30

  Abstract ▼

  The work is devoted to the analysis of mechanisms of formation of recommendations and
  evaluation of the user's reaction to them in the interactive mode of work with the geoinformation
  system. 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 task definition and ambiguity of decision evaluation. Users are often faced with problems that do not
  have a clear formulation. To try to solve them, it is necessary not only to designate the direction of
  solution search, but also to find an adequate sequence of tasks with clearly formulated input and
  output data. Recommendations in such cases are designed in a dialogue with the user-analyst to
  develop a strategy for finding solutions. In this paper we study a smart recommendation system
  using the experience of dialog interaction. We propose a model of adaptation to the mental image
  of the problem, which builds the user, taking into account the levels of situational awareness and
  cognitive load. The peculiarity of the model is the use of visual cartographic objects, which are
  indicators of the state of the mental image. A recommendation is represented by a set of objects
  that are introduced into the field of cartographic analysis. This implicitly induces a certain semantic
  direction of increasing situational awareness. A criterion of satisfaction with the recommendation
  is 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 information
  object, 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. Indicators
  of trend, tendency and rhythm are proposed for possible chains of contexts. The degree of
  semantic proximity of precedents to the current course of search for a solution is estimated by
  these indicators. Their use will increase the speed of adaptation

• INTELLIGENT RECOMMENDER SYSTEM FOR SPATIAL ANALYSIS

  S.L. Belyakov, А. V. Bozhenyuk, N. А. Golova, К.S. Yavorchuk, I.N. Rosenberg

  14-26

  2025-07-31

  Abstract ▼

  The work is devoted to the analysis of mechanisms of formation of recommendations and
  evaluation of the user's reaction to them in the interactive mode of work with the geoinformation
  system. 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 task definition and ambiguity of decision evaluation. Users are often faced with problems that do not
  have a clear formulation. To try to solve them, it is necessary not only to designate the direction of
  solution search, but also to find an adequate sequence of tasks with clearly formulated input and
  output data. Recommendations in such cases are designed in a dialogue with the user-analyst to
  develop a strategy for finding solutions. In this paper we study a smart recommendation system
  using the experience of dialog interaction. We propose a model of adaptation to the mental image
  of the problem, which builds the user, taking into account the levels of situational awareness and
  cognitive load. The peculiarity of the model is the use of visual cartographic objects, which are
  indicators of the state of the mental image. A recommendation is represented by a set of objects
  that are introduced into the field of cartographic analysis. This implicitly induces a certain semantic
  direction of increasing situational awareness. A criterion of satisfaction with the recommendation
  is 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 information
  object, 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. Indicators
  of trend, tendency and rhythm are proposed for possible chains of contexts. The degree of
  semantic proximity of precedents to the current course of search for a solution is estimated by
  these indicators. Their use will increase the speed of adaptation.