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LINGUISTIC SUMMARIES IN EVALUATING ELEMENTARY CONDITIONS AND THEIR APPLICATION IN SOFTWARE ENVIRONMENT.

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Τίτλος: LINGUISTIC SUMMARIES IN EVALUATING ELEMENTARY CONDITIONS AND THEIR APPLICATION IN SOFTWARE ENVIRONMENT.
Συγγραφείς: Sojka, Pavol
Πηγή: Proceedings of CBU in Natural Sciences & ICT; 2021, Vol. 2, p93-99, 7p
Θεματικοί όροι: Computer software development, Computer programming management, Computer programming, Business intelligence, Industrial management
Περίληψη: Data users are generally interested in two types of aggregated information: summarization of the selected attribute(s) for all considered entities and retrieval and evaluation of entities by the requirements posed on the relevant attributes. Less statistically literate users (e.g., domain experts) and the business intelligence strategic dashboards can benefit from linguistic summarization, i.e. a summary like most customers are middle-aged can be understood immediately. Evaluation of the mandatory and optional requirements of the structure P1 and most of the other posed predicates should be satisfied beneficial for analytical business intelligence dashboards and search engines in general. This work formalizes the integration of the aforementioned quantified summaries and quantified evaluation into the concept of database queries to empower their flexibility by, e.g., the nested quantified query conditions on hierarchical data structures. Later in our work, we adapted our research into practical application. We created a software environment for evaluating data based on a dataset retrieved from The Statistical Office of the Slovak republic. These datasets are aimed mainly on landscape characteristics like altitude, area sizes of towns and villages, and similar parameters. Based on user's preferences, our system recommends the most suitable place for holidays to spend on. [ABSTRACT FROM AUTHOR]
Copyright of Proceedings of CBU in Natural Sciences & ICT is the property of CBU Research Institute s.r.o. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Complementary Index
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  Data: Data users are generally interested in two types of aggregated information: summarization of the selected attribute(s) for all considered entities and retrieval and evaluation of entities by the requirements posed on the relevant attributes. Less statistically literate users (e.g., domain experts) and the business intelligence strategic dashboards can benefit from linguistic summarization, i.e. a summary like most customers are middle-aged can be understood immediately. Evaluation of the mandatory and optional requirements of the structure P1 and most of the other posed predicates should be satisfied beneficial for analytical business intelligence dashboards and search engines in general. This work formalizes the integration of the aforementioned quantified summaries and quantified evaluation into the concept of database queries to empower their flexibility by, e.g., the nested quantified query conditions on hierarchical data structures. Later in our work, we adapted our research into practical application. We created a software environment for evaluating data based on a dataset retrieved from The Statistical Office of the Slovak republic. These datasets are aimed mainly on landscape characteristics like altitude, area sizes of towns and villages, and similar parameters. Based on user's preferences, our system recommends the most suitable place for holidays to spend on. [ABSTRACT FROM AUTHOR]
– Name: Abstract
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  Group: Ab
  Data: <i>Copyright of Proceedings of CBU in Natural Sciences & ICT is the property of CBU Research Institute s.r.o. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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