Academic literature on the topic 'Relational Online Analytical Processing'

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Journal articles on the topic "Relational Online Analytical Processing"

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Sucharitha, Shetty, Dinesh Rao B., and Prabhu Srikanth. "Growth of relational model: Interdependence and complementary to big data." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 2 (2021): 1780–95. https://doi.org/10.11591/ijece.v11i2.pp1780-1795.

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A database management system is a constant application of science that provides a platform for the creation, movement, and use of voluminous data. The area has witnessed a series of developments and technological advancements from its conventional structured database to the recent buzzword, bigdata. This paper aims to provide a complete model of a relational database that is still being widely used because of its well known ACID properties namely, atomicity, consistency, integrity and durability. Specifically, the objective of this paper is to highlight the adoption of relational model approac
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Jing, Changhong, Wenjie Liu, Jintao Gao, and Ouya Pei. "Research and implementation of HTAP for distributed database." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 39, no. 2 (2021): 430–38. http://dx.doi.org/10.1051/jnwpu/20213920430.

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Data processing can be roughly divided into two categories, online transaction processing OLTP(on-line transaction processing) and online analytical processing OLAP(on-line analytical processing). OLTP is the main application of traditional relational databases, and it is some basic daily transaction processing, such as bank pipeline transactions and so on. OLAP is the main application of the data warehouse system, it supports some more complex data analysis operations, focuses on decision support, and provides popular and intuitive analysis results. As the amount of data processed by enterpri
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Alkharouf, Nadim W., D. Curtis Jamison, and Benjamin F. Matthews. "Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases." Journal of Biomedicine and Biotechnology 2005, no. 2 (2005): 181–88. http://dx.doi.org/10.1155/jbb.2005.181.

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Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest
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Hazboun, Fadi H., Majdi Owda, and Amani Yousef Owda. "A Natural Language Interface to Relational Databases Using an Online Analytic Processing Hypercube." AI 2, no. 4 (2021): 720–37. http://dx.doi.org/10.3390/ai2040043.

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Structured Query Language (SQL) is commonly used in Relational Database Management Systems (RDBMS) and is currently one of the most popular data definition and manipulation languages. Its core functionality is implemented, with only some minor variations, throughout all RDBMS products. It is an effective tool in the process of managing and querying data in relational databases. This paper describes a method to effectively automate the conversion of a data query from a Natural Language Query (NLQ) to Structured Query Language (SQL) with Online Analytical Processing (OLAP) cube data warehouse ob
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Redouane, Esbai, Hakkou Soufiane, and Achraf Habri Mohamed. "Modeling and automatic generation of data warehouse using model-driven transformation in business intelligence process." Modeling and automatic generation of data warehouse using model-driven transformation in business intelligence process 30, no. 3 (2023): 866–1874. https://doi.org/10.11591/ijeecs.v30.i3.pp1866-1874.

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The work presented in this paper focuses on the modeling and implementation of business intelligence processes, specifically how to apply model-driven architecture (MDA) throughout the entire development process of a data warehouse to automatically generate the multidimensional schema. As a result, this work specifies different rules for automating the process of obtaining an online analytical processing (OLAP) cube and implementing it using a collection of metamodels and automatic transformations. The data warehouse relational and OLAP cube models are then created using a model transformation
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Lau, T. W., C. L. Hui, S. F. Ng, K. L. Moon, and G. Taylor. "An implication of e-commerce in textile and clothing industries: a relational Online Analytical Processing (OLAP) approach." International Journal of Information Technology and Management 7, no. 3 (2008): 231. http://dx.doi.org/10.1504/ijitm.2008.017603.

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Niemi, Timo, Turkka Näppilä, and Kalervo Järvelin. "A relational data harmonization approach to XML." Journal of Information Science 35, no. 5 (2009): 571–601. http://dx.doi.org/10.1177/0165551509104231.

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There are numerous approaches for integrating data from heterogeneous data sources. A common background assumption is that the data sources remain quite stable and are known in advance. Hence an integration system can be built to manipulate them. In practice there is, however, often a demand for supporting ad hoc information needs concerning unexpected autonomous data sources containing volatile data. A different approach is therefore needed. We propose that semantically similar data are harmonized when extracting data from XML-based data sources. We introduce a constructor algebra, which is a
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Esbai, Redouane, Soufiane Hakkou, and Mohamed Achraf Habri. "Modeling and automatic generation of data warehouse using model-driven transformation in business intelligence process." Indonesian Journal of Electrical Engineering and Computer Science 30, no. 3 (2023): 1866. http://dx.doi.org/10.11591/ijeecs.v30.i3.pp1866-1874.

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The work presented in this paper focuses on the modeling and implementation of business intelligence processes, specifically how to apply model-driven architecture (MDA) throughout the entire development process of a data warehouse to automatically generate the multidimensional schema. As a result, this work specifies different rules for automating the process of obtaining an online analytical processing (OLAP) cube and implementing it using a collection of metamodels and automatic transformations. The data warehouse relational and OLAP cube models are then created using a model transformation
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Martinez-Mosquera, Diana, Rosa Navarrete, Sergio Luján-Mora, Lorena Recalde, and Andres Andrade-Cabrera. "Integrating OLAP with NoSQL Databases in Big Data Environments: Systematic Mapping." Big Data and Cognitive Computing 8, no. 6 (2024): 64. http://dx.doi.org/10.3390/bdcc8060064.

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The growing importance of data analytics is leading to a shift in data management strategy at many companies, moving away from simple data storage towards adopting Online Analytical Processing (OLAP) query analysis. Concurrently, NoSQL databases are gaining ground as the preferred choice for storing and querying analytical data. This article presents a comprehensive, systematic mapping, aiming to consolidate research efforts related to the integration of OLAP with NoSQL databases in Big Data environments. After identifying 1646 initial research studies from scientific digital repositories, a t
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Martinez-Mosquera, Diana, Rosa Navarrete, Sergio Luján-Mora, Lorena Recalde, and Andres Andrade-Cabrera. "Integrating OLAP with NoSQL Databases in Big Data Environments: Systematic Mapping." Big Data and Cognitive Computing 8, no. 6 (2024): 1–29. https://doi.org/10.3390/bdcc8060064.

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The growing importance of data analytics is leading to a shift in data management strategy at many companies, moving away from simple data storage towards adopting Online Analytical Processing (OLAP) query analysis. Concurrently, NoSQL databases are gaining ground as the preferred choice for storing and querying analytical data. This article presents a comprehensive, systematic mapping, aiming to consolidate research efforts related to the integration of OLAP with NoSQL databases in Big Data environments. After identifying 1646 initial research studies from scientific digital repositories, a t
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Dissertations / Theses on the topic "Relational Online Analytical Processing"

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Zhao, Hongyan. "A visualization tool to support Online Analytical Processing." [Gainesville, Fla.] : University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE0000622.

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Kraft, Tobias. "Rewrite-Strategien für generierte Anfragesequenzen im Online Analytical Processing." [S.l. : s.n.], 2002. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB9967003.

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Marquardt, Justus. "Metadatendesign zur Integration von online analytical processing in das Wissensmanagement." Hamburg Kovač, 2007. http://www.verlagdrkovac.de/978-3-8300-3598-5.htm.

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Marquardt, Justus. "Metadatendesign zur Integration von Online Analytical Processing in das Wissensmanagement /." Hamburg : Kovač, 2008. http://www.verlagdrkovac.de/978-3-8300-3598-5.htm.

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Sapia, Carsten. "PROMISE modeling and predicting user behavior for online analytical processing applications /." [S.l.] : [s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=962681628.

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Kamath, Akash S. "An efficient algorithm for caching online analytical processing objects in a distributed environment." Ohio : Ohio University, 2002. http://www.ohiolink.edu/etd/view.cgi?ohiou1174678903.

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Schwarz, Holger. "Integration von Data-Mining und online analytical processing : eine Analyse von Datenschemata, Systemarchitekturen und Optimierungsstrategien /." [S.l. : s.n.], 2003. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10720634.

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Tocci, Gabriel. "A Comparison of Leading Database Storage Engines in Support of Online Analytical Processing in an Open Source Environment." Digital Commons @ East Tennessee State University, 2013. https://dc.etsu.edu/etd/1111.

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Online Analytical Processing (OLAP) has become the de facto data analysis technology used in modern decision support systems. It has experienced tremendous growth, and is among the top priorities for enterprises. Open source systems have become an effective alternative to proprietary systems in terms of cost and function. The purpose of the study was to investigate the performance of two leading database storage engines in an open source OLAP environment. Despite recent upgrades in performance features for the InnoDB database engine, the MyISAM database engine is shown to outperform the InnoDB
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Chomo, Michal. "Optimalizace zpracování dat o síti Tor pomocí OLAP." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403126.

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Tor is a distributed network providing privacy and anonymity on the Internet. Information about Tor is publicly available in a form of consensus documents. Existing tools that are able to display this information do not provide both historical and detailed view of it. A tool named Consensus Parser that provides a detailed, historical view of this information and extends it with geolocation and DNS information, was created as a part of TARZAN research project at Brno University of Technology. It stores the information in regular files on disk and makes it accessible via REST API. This thesis ex
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Rausch, Philip. "Predicate-induced semantic prominence in online argument linking: experiments on affectedness and analytical tools." Doctoral thesis, Humboldt-Universität zu Berlin, 2018. http://dx.doi.org/10.18452/19305.

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Teil I dieser Arbeit untersucht Effekte einer semantischen Eigenschaft von syntaktisch transitiven Prädikaten auf die Satzverarbeitung: den Grad der Affiziertheit, den solch ein Prädikat für eines seiner Argumente impliziert, also das Ausmaß in dem ein Teilnehmer eine Zustandsveränderung während des ausgedrückten Ereignisses erfährt. Drei Experimente (zu Akzeptabilitätsurteilen, Lesezeiten & ereigniskorrelierten Potentialen [EKP]) überprüften den Einfluss von Affiziertheit auf die lexikalisch-semantische Verarbeitung des Prädikats und die Integration folgender Argument-Nominalphrasen (NPn) bei
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Books on the topic "Relational Online Analytical Processing"

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Burgard, Martin. Anwendungspotentiale des Online Analytical Processing Im Personalbereich. GRIN Verlag GmbH, 2008.

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Konzepte und Werkzeuge Zum Online Analytical Processing. GRIN Verlag GmbH, 2010.

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Wang, Lingyu, Sushil Jajodia, and Duminda Wijesekera. Preserving Privacy in On-Line Analytical Processing. Springer, 2010.

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Röhm, Uwe. Online analytical processing with a cluster of databases. 2002.

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Parker, Philip M. The 2007-2012 World Outlook for Online Analytical Processing (OLAP). ICON Group International, Inc., 2006.

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Parker, Philip M. The 2007-2012 Outlook for Online Analytical Processing (OLAP) in India. ICON Group International, Inc., 2006.

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Parker, Philip M. The 2007-2012 Outlook for Online Analytical Processing (OLAP) in Japan. ICON Group International, Inc., 2006.

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Parker, Philip M. The 2007-2012 Outlook for Online Analytical Processing (OLAP) in Greater China. ICON Group International, Inc., 2006.

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Parker, Philip M. The 2007-2012 Outlook for Online Analytical Processing (OLAP) in the United States. ICON Group International, Inc., 2006.

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Bibliographic post-processing with the TIS intelligent gateway: Analytical and communication capabilities. DTIC, 1986.

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Book chapters on the topic "Relational Online Analytical Processing"

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Dawson, Catherine. "Online analytical processing." In A–Z of Digital Research Methods. Routledge, 2019. http://dx.doi.org/10.4324/9781351044677-36.

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Abelló, Alberto, and Oscar Romero. "Online Analytical Processing." In Encyclopedia of Database Systems. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_252.

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Shekhar, Shashi, and Hui Xiong. "Spatial Online Analytical Processing." In Encyclopedia of GIS. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_1289.

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Taniar, David, and Wenny Rahayu. "Online Analytical Processing (OLAP)." In Data-Centric Systems and Applications. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81979-8_19.

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Mikšovský, Petr, and Zdenèk Kouba. "GOLAP - Geographical Online Analytical Processing." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44759-8_44.

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Jhaveri, Darpan S. "Online Analytical Processing in Accounting." In Business Intelligence Techniques. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24700-5_6.

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Scholl, Marc H., Svetlana Mansmann, Matteo Golfarelli, and Stefano Rizzi. "Visual Online Analytical Processing (OLAP)." In Encyclopedia of Database Systems. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_447-3.

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Scholl, Marc H., Svetlana Mansmann, Matteo Golfarelli, and Stefano Rizzi. "Visual Online Analytical Processing (OLAP)." In Encyclopedia of Database Systems. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_447.

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Lehner, Wolfgang. "‘Data Warehouse’ und ‘Online Analytical Processing’." In Multidimensionale Datenbanksysteme. Vieweg+Teubner Verlag, 1999. http://dx.doi.org/10.1007/978-3-322-86766-7_2.

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Jukic, Nenad, Boris Jukic, and Mary Malliaris. "Online Analytical Processing (OLAP) for Decision Support." In Handbook on Decision Support Systems 1. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-48713-5_13.

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Conference papers on the topic "Relational Online Analytical Processing"

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Dimić, Gabrijela, Ivana Milošević, and Ljiljana Pecić. "Big Data Analytics Process Implementation on a Educational Data Set Extracted from Online Testing System." In 9th International Scientific Conference Technics and Informatics in Education. University of Kragujevac, Faculty of Technical Sciences Čačak, 2022. http://dx.doi.org/10.46793/tie22.229d.

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The paper presents an application of the big data analytics process on a data extracted from the educational system for online testing. The procedure of data migration to a non-relational system was implemented. Big data analytics process was realized through query processing in MongoDB and analysis results visualization in Microsoft Power BI. The contribution of the research presented in this paper refers to the importance of applying the big data concept for analyze data set extracted from educational systems in order to discover information and knowledge important for improving the efficien
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Perach, Ben, Ronny Ronen, and Shahar Kvatinsky. "Accelerating Relational Database Analytical Processing with Bulk-Bitwise Processing-in-Memory." In 2023 21st IEEE Interregional NEWCAS Conference (NEWCAS). IEEE, 2023. http://dx.doi.org/10.1109/newcas57931.2023.10198122.

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Perach, Ben, Ronny Ronen, and Shahar Kvatinsky. "Enabling Relational Database Analytical Processing in Bulk-Bitwise Processing-In-Memory." In 2023 IEEE 36th International System-on-Chip Conference (SOCC). IEEE, 2023. http://dx.doi.org/10.1109/socc58585.2023.10256706.

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Tinnefeld, Christian, Donald Kossmann, Martin Grund, et al. "Elastic online analytical processing on RAMCloud." In the 16th International Conference. ACM Press, 2013. http://dx.doi.org/10.1145/2452376.2452429.

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Ivanova, Malinka, Carmen Holotescu, Gabriela Grosseck, and Catalin Iapa. "RELATIONS BETWEEN LEARNING ANALYTICS AND DATA PRIVACY IN MOOCS." In eLSE 2016. Carol I National Defence University Publishing House, 2016. http://dx.doi.org/10.12753/2066-026x-16-178.

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Massive Open Online Courses (MOOCs), as a new educational trend, attract worldwide a huge number of learners giving them appropriate knowledge according to personal needs. Learners are stimulated to be active participants and facilitated to create distributed learning communities through: sharing opinions and setting preferences; analyzing, annotating and translating learning materials; participating in interactive gaming exercises; communicating with other participants, tutors and guest lectures; preparing and submitting practical assignments; group working and peer rewieving; proposing other
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Xie, Zhongle, Hongbin Ying, Cong Yue, Meihui Zhang, Gang Chen, and Beng Chin Ooi. "Cool, a COhort OnLine analytical processing system." In 2020 IEEE 36th International Conference on Data Engineering (ICDE). IEEE, 2020. http://dx.doi.org/10.1109/icde48307.2020.00056.

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Correia, Jose, Maribel Yasmina Santos, Carlos Costa, and Carina Andrade. "Fast Online Analytical Processing for Big Data Warehousing." In 2018 International Conference on Intelligent Systems (IS). IEEE, 2018. http://dx.doi.org/10.1109/is.2018.8710583.

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Chen, Chen, Xifeng Yan, Feida Zhu, Jiawei Han, and Philip S. Yu. "Graph OLAP: Towards Online Analytical Processing on Graphs." In 2008 Eighth IEEE International Conference on Data Mining (ICDM). IEEE, 2008. http://dx.doi.org/10.1109/icdm.2008.30.

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Easmin, Nilufar, K. M. Azharul Hasan, and Nilufa Parvin. "An efficient implementation scheme for multidimensional online analytical processing." In 2008 11th International Conference on Computer and Information Technology (ICCIT). IEEE, 2008. http://dx.doi.org/10.1109/iccitechn.2008.4802985.

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Worth, Aidan, Aris Televantos, Nicos Evmides, Michalis P. Michaelides, and Herodotos Herodotou. "Online Analytical Processing of Port Calls for Decision Support." In 2022 23rd IEEE International Conference on Mobile Data Management (MDM). IEEE, 2022. http://dx.doi.org/10.1109/mdm55031.2022.00095.

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