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The Hybrid multidimensional-Ontological data model Based on Metagraph Approach 1

11th International Andrei P. Ershov Informatics Conference on Perspectives of System Informatics (PSI)

作者： Chernenkiy, Valeriy M. Gapanyuk, Yuriy E. Nardid, Anatoly N. Gushcha, Anton V. Fedorenko, Yuriy S. Bauman Moscow State Tech Univ Informat & Control Syst Dept Baumanskaya 2 Ya5 Moscow 105005 Russia

ISBN: (数字)9783319743134

ISBN: (纸本)9783319743134;9783319743127

This paper is aimed to overcome the limitation of the traditional multidimensional model in order to allow usage of numerical, textual and object-oriented information as multidimensional model measures. The ontological approach is reviewed. The formal definition of multidimensional approach is given. The idea of multidimensional and ontological approaches hybridization is discussed. The hybrid multidimensional-ontological data model requirements are proposed. The formal definitions of the metagraph data model and metagraph agent model are given. The examples of data metagraph and metagraph rule agent are discussed. The representation of object-oriented data structures in form of metagraph is given. The hybrid multidimensional-ontological data model based on metagraph approach is proposed. Predicate representation of metagraph model considered as a physical data model for metagraph approach implementation is given.

关键词： Ontology multidimensional data model Dimension Measure Metagraph Metagraph agent

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Research on multidimensional data model in data Warehouse

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International Journal of Technology Management 2015年第1期 120-122页

作者： Guangjie LI Guangdong Industry Technical College Guangzhou 510300 China

data structure and semantics of the traditional data model cannot effectively represent the data warehouse, it is difficult to effectively support online analytical processing （referred to as OLAP）. This paper is propose a new multidimensional data model based on the partial ordering and mapping. The data model can fully express the complex data structure and semantics of data warehouse, and provide an OLAP operation as the core of the operation of algebra, support structure in levels of complex aggregation operation sequence, which can effectively support the application of OLAE The data model supports the concept of aggregation function constraint, and provides constraint mechanism of the hierarchy aggregation function.

关键词： data warehouse data model multidimensional data model OLAP

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Movie Recommendation Using OLAP and multidimensional data model 13

Movie Recommendation Using OLAP and Multidimensional Data Mo...

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13th IFIP TC8 International Conference on Computer Information Systems and Industrial Management Applications (CISIM)

作者： Jakkhupan, Worapot Kajkamhaeng, Supasit Prince Songkla Univ Fac Sci Informat & Commun Technol Programme Hat Yai 90112 Thailand

ISBN: (纸本)9783662452370;9783662452363

This research proposes an adoption of data warehousing concepts to create a movie recommender system. The data warehouse is generated using ETL process in a desired star schema. The profiles of users and movies are created using multidimensional data model. The data are analyzed using OLAP, and the reports are generated using data mining and analysis tools. The recommended movies are selected using multi-criteria candidate selection. The movies which present the genres that match individual preference are recommended to the particular user. The multidimensional data model and OLAP provide high performance to discover the new knowledge in the big data.

关键词： Movie recommender system data warehousing MDX language OLAP multidimensional data model

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Research on multidimensional data model in data warehouse

Research on multidimensional data model in data warehouse

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2014 2nd International Conference on Computer,Electrical,and Systems Sciences,and Engineering(CESSE 2014)

作者： Guangjie Li Guangdong Industry Technical College

data structure and semantics of the traditional data model cannot effectively represent the data warehouse, it is difficult to effectively support online analytic processing(referred to as OLAP). This paper is propose a new multidimensional data model based on the partial ordering and mapping. The data model can fully express the complex data structure and semantics of data warehouse, and provide an OLAP operation as the core of the operation of algebra, support structure in levels of complex aggregation operation sequence, which can effectively support the application of OLAP. The data model supports the concept of aggregation function constraint, and provides constraint mechanism of the hierarchy aggregation function.

关键词： data warehouse data model multidimensional data model OLAP

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A multidimensional data model using the fuzzy model based on the semantic translation

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INFORMATION SYSTEMS FRONTIERS 2013年第3期15卷 351-370页

作者： Carrasco, Ramon A. Munoz-Leiva, Francisco Hornos, Miguel J. Univ Granada Dept Software Engn E-18071 Granada Spain Univ Granada Dept Mkt & Market Res E-18071 Granada Spain

With the rapid development of Web 2.0 sites such as Blogs and Wikis users are encouraged to express opinions about certain products, services or social topics over the web. There is a method for aggregating these opinions, called Opinion Aggregation, which is made up of four steps: Collect, Identify, Classify and Aggregate. In this paper, we present a new conceptual multidimensional data model based on the Fuzzy model based on the Semantic Translation to solve the Aggregate step of an Opinion Aggregation architecture, which allows exploiting the measure values resulting from integrating heterogeneous information (including unstructured data such as free texts) by means of traditional Business Intelligence tools. We also present an entire Opinion Aggregation architecture that includes the Aggregate step and solves the rest of steps (Collect, Identify and Classify) by means an Extraction, Transformation and Loading process. This architecture has been implemented in an Oracle Relational database Management System. We have applied it to integrate heterogeneous data extracted from certain high end hotels websites, and we show a case study using the collected data during several years in the websites of high end hotels located in Granada (Spain). With this integrated information, the data Warehouse user can make several analyses with the benefit of an easy linguistic interpretability and a high precision by means of interactive tools such as the dashboards.

关键词： multidimensional data model Fuzzy linguistic modelling Linguistic multidimensional data model Opinion aggregation

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Controlling the Correctness of Aggregation Operations During Sessions of Interactive Analytic Queries

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ACM JOURNAL OF data AND INFORMATION QUALITY 2023年第2期15卷 1-41页

作者： Simon, Eric Amann, Bernd Liu, Rutian Gancarski, Stephane SAP France 35 Rue dAlsace 92300 Levallois Perret France Sorbonne Univ CNRS LIP6 4 Pl Jussieu F-75005 Paris France

We present a comprehensive set of conditions and rules to control the correctness of aggregation queries within an interactive data analysis session. The goal is to extend self-service data preparation and Business Intelligence (BI) tools to automatically detect semantically incorrect aggregate queries on analytic tables and views built by using the common analytic operations including filter, project, join, aggregate, union, difference, and pivot. We introduce aggregable properties to describe for any attribute of an analytic table, which aggregation functions correctly aggregate the attribute along which sets of dimension attributes. These properties can also be used to formally identify attributes that are summarizable with respect to some aggregation function along a given set of dimension attributes. This is particularly helpful to detect incorrect aggregations of measures obtained through the use of non-distributive aggregation functions like average and count. We extend the notion of summarizability by introducing a new generalized summarizability condition to control the aggregation of attributes after any analytic operation. Finally, we define propagation rules that transform aggregable properties of the query input tables into new aggregable properties for the result tables, preserving summarizability and generalized summarizability.

关键词： Analytic queries summarizability data quality multidimensional data model interactive query sessions

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Optimizing Crop Monitoring: A data Warehouse Approach in Precision Agriculture 15

Optimizing Crop Monitoring: A Data Warehouse Approach in Pre...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Agarwal, Isha Rana, Dipti Shah, Priyanshi Dude, Aayush Patel, Pooja Avionics Lab Surat India Department of Computer Science and Engg. Surat India

ISBN: (纸本)9798350370249

Precision agriculture harnesses advanced technology and data analytics to enhance the efficiency and cost-effectiveness of agricultural production. This paper presents a comprehensive case study focused on optimizing crop monitoring through the implementation of a robust data warehouse framework. Our objective is to propose development of a system capable of seamlessly collecting, storing, and analyzing data from diverse sources, including drones, sensors, and farmer-contributed information, all integrated within a cohesive data warehouse architecture. In response to the dynamic needs of farmers, our primary aim is to facilitate the swift retrieval of crop-specific information at any developmental stage. To achieve this, we introduce a sophisticated multidimensional data model adept at managing intricate agricultural datasets. This model seamlessly integrates with modern technologies such as machine learning algorithms and decision-support systems, providing an enhanced decision-making ecosystem for farmers. In the context of this under explored subject, our proposed approach empowers farmers with precise information for informed decision-making in crop management. We anticipate that this strategy will not only enable farmers to increase yields and improve crop quality but also contribute to significant cost savings. Our research aims to pave the road for a more ecological and efficient agricultural industry by eliminating the current access gap to detailed crop life-cycle data. © 2024 IEEE.

关键词： Agricultural data Analytics Crop Monitoring data Warehouse Decision-Support Systems Drones in Agriculture multidimensional data model Precision Agriculture

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A multidimensional data warehouse design to combat the health pandemics

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Journal of data, Information and Management 2022年第3-4期4卷 371-386页

作者： Turcan, Gizem Peker, Serhat Izmir Bakircay University Izmir Turkey

The Covid-19 pandemic has brought about a new lifestyle for across the globe. Throughout this period, the use of holistic methods has become indispensable to deal with the enormous amount of data in this regard. It appears that the simplest way to tackle this issue is to spread the digitalization efforts concerning all data-based applications. Given the significance of pandemic data management, it is essential to have a data warehouse that collects, associates, and communicates these data. Containing a significant volume of structured data, warehousing can provide the necessary foundation for data mining and the development of analytical tools. To this end, the present paper proposes a data warehouse for combatting and managing pandemics, with the possibility to be enhanced for other personal or public health-related initiatives. In this research, the bottom-up data warehouse building methodology is used to construct a warehouse. A fact constellation schema model is utilized to accommodate the information ranging from citizen demographics to physician-prescribed drugs and laboratory tests. Sample queries are executed based on the proposed data warehouse for different purposes, and desired query results are obtained within proper response times. The proposed data warehouse contributes to countrywide implementation of pandemic practices and illuminates research on faster, less expensive, and safer management of citywide, nationwide, or worldwide health emergencies within a robust technical framework by governments. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022.

关键词： Covid-19 data management data mining data warehouse multidimensional data model

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Restoring Consistency in Ontological multidimensional data models via Weighted Repairs 23rd

Restoring Consistency in Ontological Multidimensional Data M...

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23rd KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES)

作者： Haque, Enamul Chiang, Fei McMaster Univ Comp & Software Hamilton ON Canada

High data quality is a prerequisite for accurate data analysis. However, data inconsistencies often arise in real data, leading to untrusted decision making downstream in the data analysis pipeline. In this paper, we study the problem of inconsistency detection and repair of the Ontology Multi-dimensional data model (OMD). We propose a framework of data quality assessment, and repair for the OMD. We formally define a weight-based repair-by-deletion semantics, and present an automatic weight generation mechanism that considers multiple input criteria. Our methods are rooted in multi-criteria decision making that consider the correlation, contrast, and conflict that may exist among multiple criteria, and is often needed in the data cleaning domain. (C) 2019 The Authors. Published by Elsevier B.V.

关键词： multidimensional data model ontology data quality weight repairs CRITIC

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A Novel Unified data modeling Method for Equipment Lifecycle Integrated Logistics Support

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SENSORS 2022年第11期22卷 4265-4265页

作者： Cui, Xuemiao Lu, Jiping Han, Yafeng Beijing Inst Technol Sch Mech Engn Beijing 100081 Peoples R China

Integrated logistics support (ILS) is of great significance for maintaining equipment operational capability in the whole lifecycle. Numerous segments and complex product objects exist in the process of equipment ILS, which gives ILS data multi-source, heterogeneous, and multidimensional characteristics. The present ILS data cannot satisfy the demand for efficient utilization. Therefore, the unified modeling of ILS data is extremely urgent and significant. In this paper, a unified data modeling method is proposed to solve the consistent and comprehensive expression problem of ILS data. Firstly, a four-tier unified data modeling framework is constructed based on the analysis of ILS data characteristics. Secondly, the Core unified data model, Domain unified data model, and Instantiated unified data model are built successively. Then, the expressions of ILS data in the three dimensions of time, product, and activity are analyzed. Thirdly, the Lifecycle ILS unified data model is constructed, and the multidimensional information retrieval methods are discussed. Based on these, different systems in the equipment ILS process can share a set of data models and provide ILS designers with relevant data through different views. Finally, the practical ILS data models are constructed based on the developed unified data modeling software prototype, which verifies the feasibility of the proposed method.

关键词： integrated logistics support metadata metamodel unified data modeling multidimensional data model

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