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    Wyświetlanie 1-3 z 3
    Tytuł:
    A new approach to storing dynamic data in relational databases using JSON
    Autorzy:
    Piech, M.
    Marcjan, R.
    Powiązania:
    https://bibliotekanauki.pl/articles/305822.pdf
    Data publikacji:
    2018
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    JSON
    Relation Databases
    EAV
    Criminal Data
    PostgreSQL
    Opis:
    JavaScript Object Notation was originally designed to transfer data; however, it soon found another use as a way to persist data in NoSQL databases. Recently, the most popular relational databases introduced JSON as native column type, which makes it easier to store and query dynamic database schema. In this paper, we review the currently popular techniques of storing data with a dynamic model with a large number of relationships between entities in relational databases. We focus on creating a simple dynamic schema with JSON in the most popular relational databases and we compare it with well-known EAV/CR data model and the document database. The results of precisely selected tests in the field of Criminal Data suggest that the use of JSON in dynamic database schema greatly simplifies queries and reduces their execution time compared to widely used approaches.
    Źródło:
    Computer Science; 2018, 19 (1); 5-22
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Pozyskiwanie wiedzy z relacyjnych baz danych: wielopodmiotowe podsumowania lingwistyczne
    Acquiring Knowledge from Relational Databases: Multi-Subject Linguistic Summaries
    Autorzy:
    Superson, Izabela
    Niewiadomski, Adam
    Powiązania:
    https://bibliotekanauki.pl/articles/589277.pdf
    Data publikacji:
    2014
    Wydawca:
    Uniwersytet Ekonomiczny w Katowicach
    Tematy:
    Programy komputerowe
    Relacyjne bazy danych
    Systemy informatyczne
    Computer programs
    Computer system
    Relation databases
    Opis:
    The aim of this article is to show how fuzzy logic based algorithms can be applied to analyze large datasets and present its results in a human-friendly form: using natural language. A new concept of linguistic summaries is demonstrated: multi-subject linguistic summaries of relational databases, that extends the classic manner. This paper focuses on new, interesting forms of linguistic summaries, which are represented by equations (4), (11), (15) and (18). This article also contains discussion about calculating degrees of truth of the new forms. From the potential end user point of view simplified form of presenting results using natural language expressions is the most important thing. This paper includes demonstration and description of standalone application that generates analysis of large dataset and presents results using short and intuitive expressions in natural language. Possibilities given by the multi-subject linguistic summaries, e.g. description and comparison of more than one subject in one summarization, makes them great extension and complementation of existing forms of linguistic summaries.
    Źródło:
    Studia Ekonomiczne; 2014, 199; 297-312
    2083-8611
    Pojawia się w:
    Studia Ekonomiczne
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Attribute-oriented denazification of fuzzy database tuples with categorical entries
    Autorzy:
    Angryk, R. A.
    Powiązania:
    https://bibliotekanauki.pl/articles/970948.pdf
    Data publikacji:
    2009
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    defuzzification of fuzzy tuples
    non-atomic categorical data entries
    attribute-oriented induction
    fuzzy databases
    fuzzy similarity relation
    Opis:
    We are investigating the ability to data mine fuzzy tuples, which are often utilized to represent uncertainty about the registered information. We discuss different aspects of fuzzy databases and comment on practical advantages of the model we utilized in our research. Motivated by a well known technique called Attribute-Oriented Induction, which has been developed for summarization of ordinary relational databases, we propose a new heuristic algorithm, allowing attribute-oriented defuzzification of fuzzy database tuples to the form acceptable for many regular (i.e. atomic values based) data mining algorithms. Significant advantages of our approach to defuzzification of fuzzy database tuples include: (1) its intuitive character of fuzzy tuples' interpretation, (2) a unique capability of incorporating background knowledge, implicitly stored in the fuzzy database models in the form of fuzzy similarity relation, directly into the imprecise data interpretation process, (3) transformation of fuzzy tuples to a format easy to process by regular data mining algorithms, and (4) a good scalability for time-efficient treatment of large datasets containing non-atomic, categorical data entries.
    Źródło:
    Control and Cybernetics; 2009, 38, 2; 419-453
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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