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Genre-Based Music Language Modeling with Latent Hierarchical Pitman-Yor Process Allocation
PublicationIn this work we present a new Bayesian topic model: latent hierarchical Pitman-Yor process allocation (LHPYA), which uses hierarchical Pitman-Yor pr ocess priors for both word and topic distributions, and generalizes a few of the existing topic models, including the latent Dirichlet allocation (LDA), the bi- gram topic model and the hierarchical Pitman-Yor topic model. Using such priors allows for integration of -grams with a topic model,...
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Genre-Based Music Language Modeling with Latent Hierarchical Pitman-Yor Process Allocation
PublicationIn this work we present a new Bayesian topic model: latent hierarchical Pitman-Yor process allocation (LHPYA), which uses hierarchical Pitman-Yor pr ocess priors for both word and topic distributions, and generalizes a few of the existing topic models, including the latent Dirichlet allocation (LDA), the bi- gram topic model and the hierarchical Pitman-Yor topic model. Using such priors allows for integration of -grams with a topic...
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The Algorithm of Modelling and Analysis of Latent Semantic Relations: Linear Algebra vs. Probabilistic Topic Models
PublicationThis paper presents the algorithm of modelling and analysis of Latent Semantic Relations inside the argumentative type of documents collection. The novelty of the algorithm consists in using a systematic approach: in the combination of the probabilistic Latent Dirichlet Allocation (LDA) and Linear Algebra based Latent Semantic Analysis (LSA) methods; in considering each document as a complex of topics, defined on the basis of separate...
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The algorithm of building the hierarchical contextual framework of textual corpora
PublicationThis paper presents an approach for Modeling the Latent Semantic Relations. The approach is based on advantages of two computational approaches: Latent Semantic Analysis and Latent Dirichlet Allocation. The scientific question about the possibility of reducing the influence of these Methods limitation on the Quality of the Latent Semantic Relations Analysis Results is raised. The case study for building the Two-level Hierarchical Contextual...
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublicationTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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The Crowd as a Source of Knowledge - From User Feedback to Fulfilling Requirements
PublicationCrowd-based and data-intensive requirements engineering (RE) strategy is an approach for gathering and analyzing information from the general public or the so-called crowd to derive validated user requirements. This study aims to conceptualize the process of analyzing information from a crowd to achieve the fulfillment of user requirements. The created model is based on the ADO framework (Antecedents-Decisions-Outcomes). In the...
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Modeling the Customer’s Contextual Expectations Based on Latent Semantic Analysis Algorithms
PublicationNowadays, in the age of Internet, access to open data detects the huge possibilities for information retrieval. More and more often we hear about the concept of open data which is unrestricted access, in addition to reuse and analysis by external institutions, organizations and people. It’s such information that can be freely processed, add another data (so-called remix) and then published. More and more data are available in text...
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Optimised allocation of actuators for DWDS
PublicationThis paper addresses the problem of actuators’ allocation within networked structured system, namely allocation of disinfectant booster stations within Drinking Water Distribution System (DWDS), under receding horizon optimised control – Model Predictive Control (MPC) to be exact. The allocation task is kept within dynamic multiobjective optimisation framework. The MPC is defined as a single objective predictive operator. Two numerical...
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Dirichlet-to-Neumann and Neumann-to-Dirichlet methods for eigenvalues and eigenfunctions of the Laplace operator
PublicationPrzedstawiono dwie metody służące do znajdowania wartości własnych i funkcji własnych równania Helmholtza w ograniczonej dziedzinie. Punktem wyjścia była konstrukcja zasad wariacyjnych uwzględniających możliwość stosowania nieciągłych funkcji próbnych (lub funkcji próbnych o nieciągłych pochodnych normalnych). Następny etap to wykorzystanie powierzchniowych operatorów całkowych typu DtN i NtD. Efektywność metod przetestowano na...
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Dirichlet-to-Neumann and Neumann-to-Dirichlet embedding methods for bound states of the Dirac equation
PublicationZaprezentowano uogólnienie formalizmu operatorów Dirichleta-Neumanna (DtN) i Neumanna-Dirichleta (NtD) na przypadek równania Diraca. Przedstawiono zastosowanie tego formalizmu do znajdowania poziomów energetycznych cząstki Diraca związanej w potencjale.