Fuzzy Ontology-based Approach for the Requirements Query Imprecision Assessment in Data Warehouse Design Process near Negative Fuzzy Operator

Abstract

Abstract-The vagueness in decision-making may be due to ambiguity in the decisional requirements expression. Therefore, in the literature dealing with vagueness in decision systems, studies were concentrated on data vagueness and not on decision requirements. In order to evaluate the expression in decision-making requirements and in order to improve the data warehouses design quality, this paper presents a rigorous fuzzy ontologybased solution.Based on the latest Zadeh theory "Ref.[1]", Authors in "Ref. [2.3]", propose a solution consisting in using ontologies to provide "an understanding of how the meaning of a proposal can be composed of the meaning of its constituents. One of the limitations of this solution is the fuzziness presence only at the adjective sentence. In some sense, our proposal can be seen as a continuation of that work. We limit our study, in this paper to the "Near negative" operator case. To the best of our knowledge, this case has not been addressed yet in the data warehouse context.

Multiprocessing as a Way to Optimize Queries

“…Or, in the case of not fully using the functionality, such as only updating prices, availability of goods and some categories, solve the issue by contacting the IP of your own development using the Job class (Fig. 4) Let's move on to solving the issue of multiprocessing and optimization of the web application developed on Laravel [20,21]. With the help of this framework, it is possible to make settings so that in the Config directory, where the configuration file is located, a separate configuration file database_connect.php was specified, where the settings for a new connection will be specified in this file, so that the job is executed on a specific connection.…”