A SEARCHING ALGORITHM FOR TEXT WITH MISTAKES

The paper contains a new text searching method representing modification of the Boyer-Moore algorithm and enabling a user to find the places in the text where the given substring occurs maybe with possible errors, that is the string in text and a query may not coincide but nevertheless are identical. The idea consists in division of the searching process in two phases: at the first phase a fuzzy variant of the Boyer–Moore algorithm is performed; at the second phase the Dice metrics is used. The advantage of suggested technique in comparison with the known methods using the fixed value of the mistakes number is that it 1) does not perform precomputation of the auxiliary table of the sizes comparable to the original text sizes and 2) it more flexibly catches the semantics of the erroneous text substrings even for a big number of mistakes. This circumstance extends possibilities of the Boyer–Moore method by addmitting a bigger amount of possible mistakes in text and preserving text semantics. The suggested method provides also more accurate regulation of the upper boundary for the text mistakes which differs it from the known methods with fixed value of the maximum number of mistakes not depending on the text sizes. Moreover, this upper boundary is defined as Levenshtein distance not suitable for evaluating a relevance of the founded text and a query, while the Dice metrics provides such a relevance. In fact, if maximum Levenshtein distanse is 3 then how one can judge if this value is big or small to provide relevance of the search results. Consequently, the suggested method is more flexible, enables one to find relevant answers even in case of a big number of mistakes in text. The efficiency of the suggested method in the worst case is O(nc) with constant c defining the biggest allowable number of mistakes.The paper contains a new text searching method representing modification of the Boyer-Moore algorithm and enabling a user to find the places in the text where the given substring occurs maybe with possible errors, that is the string in text and a query may not coincide but nevertheless are identical. The idea consists in division of the searching process in two phases: at the first phase a fuzzy variant of the Boyer–Moore algorithm is performed; at the second phase the Dice metrics is used. The advantage of suggested technique in comparison with the known methods using the fixed value of the mistakes number is that it 1) does not perform precomputation of the auxiliary table of the sizes comparable to the original text sizes and 2) it more flexibly catches the semantics of the erroneous text substrings even for a big number of mistakes. This circumstance extends possibilities of the Boyer–Moore method by addmitting a bigger amount of possible mistakes in text and preserving text semantics. The suggested method provides also more accurate regulation of the upper boundary for the text mistakes which differs it from the known methods with fixed value of the maximum number of mistakes not depending on the text sizes. Moreover, this upper boundary is defined as Levenshtein distance not suitable for evaluating a relevance of the founded text and a query, while the Dice metrics provides such a relevance. In fact, if maximum Levenshtein distanse is 3 then how one can judge if this value is big or small to provide relevance of the search results. Consequently, the suggested method is more flexible, enables one to find relevant answers even in case of a big number of mistakes in text. The efficiency of the suggested method in the worst case is O(nc) with constant c defining the biggest allowable number of mistakes

Realizing the consciousness in artificial intelligence

A new two-unit model of a "concious" neuron is presented to be realised in AL-based systems/ The main difference from the known paradigms is the admission of the phenomenon of self-perception by the neuron of its own state, displayed by its electromagnetic cloud. This phenomenoncreates in given representation the nature of consciusness. Some consequences of the hypothesis are considered

Метод извлечения информации из резюме

An approach to information extraction from short and poorly structured text document such as resume (CV) is suggested. The computer-based resume processing is an actual interesting application problem. There are a number of web-sites for centralized CVs allocation oriented at different employers. Oftenly, an employer is most interested in some peculiar features connected to professional achievements and knowledges of the applicant, not a resume as a whole. Extraction of such peculiar information from CV is a problem itself especially if the CV is organized in an arbitrary form, poorly structured and contains grammatic mistakes. The suggested paper is devoted to processsing the CVs of this type. A short review is given of the existing approaches to information extraction from CV and the key-word-based approach is selected and founded from the viewpoint of efficient information extraction the employer is interested in. The specificity of the approach is emphasized for the case when keywords define text blocks with a definite conceptual content. In this case one more problem arrises connected to text blocks definition. An approach based on clustering technique is suggested, so each cluster is associated with the corresponding text block in the raw CV. At the same time, the technical realization of the approach suggested remains open for future investigations. The examples are given illustrating text extraction technique to get a relevant answer to arbitrary employer query addressed to CV

Distorted qr-code correction algorithm

This article mainly study about the problems of image tilt and geometric distortion that may be encountered in the identification process of QR-code symbol characteristics are used to rotate and orient the image

МОДЕЛЬ ПРОГНОЗИРОВАНИЯ С ИСПОЛЬЗОВАНИЕМ НЕЧЕТКОГО ОБУЧАЮЩЕГО МНОЖЕСТВА

A problem of constructing a numeric forecasting evaluator on the basis of a fuzzy learning set is considered. The stated general problem is connected to the definition of the missing fuzzy vector co-ordinates and their evaluation. The general formulation is divided into two tasks: to build a method producing missing fuzzy forecasting values with expected value of a fuzzy measure and forecasting quality estimation. The given mathematical backgrounds are based on the model of a multidimensional crisp classifier and its usage for the fuzzy measure definition with the following evaluation on the basis of the fuzzy vectors probabilities by R. Yager.Рассматривается задача построения численного прогноза с использованием обучающего нечеткого множества. Поставленная в статье общая проблема связана с доопределением значений нечеткого вектора и его оценкой. При этом решается две задачи: разработка метода для генерации нечеткого прогнозного значения с ожидаемым (в статистическом смысле) значением нечеткой меры и оценка качества прогноза. Представленный математический аппарат базируется на технике построения четкого многомерного классификатора и его использования для определения нечеткой меры принадлежности с последующей оценкой вероятностей нечетких векторов по Р. Ягеру

Electronic Structure and Magnetic Exchange Coupling in Ferromagnetic Full Heusler Alloys

Density-functional studies of the electronic structures and exchange interaction parameters have been performed for a series of ferromagnetic full Heusler alloys of general formula Co$_2$MnZ (Z = Ga, Si, Ge, Sn), Rh$_2$MnZ (Z = Ge, Sn, Pb), Ni$_2$MnSn, Cu$_2$MnSn and Pd$_2$MnSn, and the connection between the electronic spectra and the magnetic interactions have been studied. Different mechanisms contributing to the exchange coupling are revealed. The band dependence of the exchange parameters, their dependence on volume and valence electron concentration have been thoroughly analyzed within the Green function technique.Comment: 9 figures, 6 table

Оценка приоритетов управлений на основе матрицы парных сравнений

The article contains a description of the model and approach for determining the weights of controls (other objects) based on a matrix of pairwise comparisons. The initial data in the matrix of paired comparisons implicitly specify interval estimates for comparison of controls. Interval estimates can be constructed relatively easily using Harrington's fuzzy metric scale. A heuristic method for determining the priorities of controls is proposed, which seeks to obtain weights (priorities) of controls that deviate minimally from the boundary values of the weight intervals.The latter are easy to find using the system of relations, on the basis of which the matrix of pairwise comparisons of controls is built. To assess the statistical adequacy of the found control priorities, the determination coefficient is used, the value of which at the level of 80 % and above is considered practically acceptable for applications. The critical value of the coefficient of determination can be determined, for example, using the Fisher criterion. If the conditions of statistical adequacy are not met, the initial data in the matrix of paired comparisons should be revised. An example is provided to illustrate the method described in the article. The main advantages of the approach described in the article are the flexibility of the choice of interval estimates for pairwise comparison of controls, the relative simplicity of computational calculations, and the ability to control the calculation results using statistical criteria. The described method develops the authors' approach to the adoption of anti-crisis management by adapting management priorities to the conditions of the production system and its environment.В статье содержится описание модели и подхода для определения весов управлений (иных объектов) на основе матрицы парных сравнений. Исходные данные в матрице парных сравнений в неявном виде задают интервальные оценки для сравнения управлений. Интервальные оценки можно сравнительно просто построить, используя нечеткую метрическую шкалу Харрингтона. Предлагается эвристический метод определения приоритетов управлений, который стремится получить веса (приоритеты) управлений, минимально отклоняющиеся от граничных значений интервалов весов. Последние легко отыскать с помощью системы отношений, на базе которых построена матрица парных сравнений управлений. Для оценки статистической адекватности найденных приоритетов управлений используется коэффициент детерминации, значение которого на уровне 80 % и выше считается практически приемлемым для приложений. Критическое значение коэффициента детерминации может быть определено, например, с помощью критерия Фишера. При невыполнении условий статистической адекватности следует пересмотреть исходные данные в матрице парных сравнений. Приведен пример, иллюстрирующий описанный в статье метод. Основными достоинствами изложенного в статье подхода являются гибкость выбора интервальных оценок при парном сравнении управлений, относительная простота вычислительных расчетов, возможность контроля результатов расчетов с помощью статистических критериев. Описанный метод развивает подход авторов к принятию антикризисных управлений за счет адаптации приоритетов управлений к условиям производственной системы и ее окружения

Evaluation of Control Priorities Based on a Matrix of Paired Comparisons

В статье содержится описание модели и подхода для определения весов управлений (иных объектов) на основе матрицы парных сравнений. Исходные данные в матрице парных сравнений в неявном виде задают интервальные оценки для сравнения управлений. Интервальные оценки можно сравнительно просто построить, используя нечеткую метрическую шкалу Харрингтона. Предлагается эвристический метод определения приоритетов управлений, который стремится получить веса (приоритеты) управлений, минимально отклоняющиеся от граничных значений интервалов весов. Последние легко отыскать с помощью системы отношений, на базе которых построена матрица парных сравнений управлений. Для оценки статистической адекватности найденных приоритетов управлений используется коэффициент детерминации, значение которого на уровне 80 % и выше считается практически приемлемым для приложений. Критическое значение коэффициента детерминации может быть определено, например, с помощью критерия Фишера. При невыполнении условий статистической адекватности следует пересмотреть исходные данные в матрице парных сравнений. Приведен пример, иллюстрирующий описанный в статье метод. Основными достоинствами изложенного в статье подхода являются гибкость выбора интервальных оценок при парном сравнении управлений, относительная простота вычислительных расчетов, возможность контроля результатов расчетов с помощью статистических критериев. Описанный метод развивает подход авторов к принятию антикризисных управлений за счет адаптации приоритетов управлений к условиям производственной системы и ее окружения. The article contains a description of the model and approach for determining the weights of controls (other objects) based on a matrix of pairwise comparisons. The initial data in the matrix of paired comparisons implicitly specify interval estimates for comparison of controls. Interval estimates can be constructed relatively easily using Harrington's fuzzy metric scale. A heuristic method for determining the priorities of controls is proposed, which seeks to obtain weights (priorities) of controls that deviate minimally from the boundary values of the weight intervals.The latter are easy to find using the system of relations, on the basis of which the matrix of pairwise comparisons of controls is built. To assess the statistical adequacy of the found control priorities, the determination coefficient is used, the value of which at the level of 80 % and above is considered practically acceptable for applications. The critical value of the coefficient of determination can be determined, for example, using the Fisher criterion. If the conditions of statistical adequacy are not met, the initial data in the matrix of paired comparisons should be revised. An example is provided to illustrate the method described in the article. The main advantages of the approach described in the article are the flexibility of the choice of interval estimates for pairwise comparison of controls, the relative simplicity of computational calculations, and the ability to control the calculation results using statistical criteria. The described method develops the authors' approach to the adoption of anti-crisis management by adapting management priorities to the conditions of the production system and its environment