Results

Found 29 articles

Clear filters

Cost-based Optimization of Multistore Query Plans
PDF
2023 | Information Systems Frontiers | Citations: 0
Authors: Forresi, Chiara; Francia, Matteo; Gallinucci, Enrico; Golfarelli, Matteo

Abstract: Multistores are data management systems that enable query processing across diff ... Expand

Abstract: Multistores are data management systems that enable query processing across different and heterogeneous databases; besides the distribution of data, complexity factors like schema heterogeneity and data replication must be resolved through integration and data fusion activities. Our multistore solution relies on a dataspace to provide the user with an integrated view of the available data and enables the formulation and execution of GPSJ queries. In this paper, we propose a technique to optimize the execution of GPSJ queries by formulating and evaluating different execution plans on the multistore. In particular, we outline different strategies to carry out joins and data fusion by relying on different schema representations; then, a self-learning black-box cost model is used to estimate execution times and select the most efficient plan. The experiments assess the effectiveness of the cost model in choosing the best execution plan for the given queries and exploit multiple multistore benchmarks to investigate the factors that influence the performance of different plans. Collapse

Semantic filters: MongoDB

Topics: database system MongoDB PostgreSQL document database relational database

Methods: computational algorithm experiment case study regression analysis method longitudinal research
Navigating Workload Compatibility Between a Recommender System and a NoSQL Database: An Interactive Tutorial
PDF
2023 | Communications of the Association for Information Systems | Citations: 0
Authors: Kayhan, Varol; Berndt, Donald

Abstract: Follow this and additional works at: https://aisel.aisnet.org/cais Recommended ... Expand

Abstract: Follow this and additional works at: https://aisel.aisnet.org/cais Recommended Citation Recommended Citation Abstract:In this tutorial, the issue of compatibility between a big data storage technology and an analytic workload is explored using a fictitious streaming company as an example. The tutorial offers an interactive approach to help students understand the importance of considering workload compatibility when adopting new technologies. We provide instructors with the following: two Jupyter Notebooks that analyze compatibility, a detailed instructor guide on how to execute these notebooks, lessons learned, and appendices containing solutions and explanations. This tutorial provides a valuable resource for instructors teaching courses in database systems, big data, and analytic concepts, helping students develop practical skills to navigate effectively the complexities of big data technologies. Collapse

Semantic filters: MongoDB

Topics: database system document database recommender system collaborative filtering nosql database

Methods: database modeling design science survey
A Chat-based personal recommendation mechanism with opinion intelligence

2023 | Americas Conference on Information Systems | Citations: 0
Authors: Li, Yung-Ming; hsieh, chin yu; Hsu, Cheng-Chi

Abstract: A Chat-based personal recommendation mechanism with opinion intelligence" (2023 ... Expand

Abstract: A Chat-based personal recommendation mechanism with opinion intelligence" (2023). AbstractWith the rapid development of the Internet and mobile devices, users around the world have accumulated a large amount of comment data on the Internet. Nowadays, users tend to search for information on the Internet before making purchase decisions. How to provide personalized services while avoiding information overload has gradually become an important issue. This study proposes a dialogue-based personalized recommendation mechanism with opinion intelligence. In addition to understanding user preferences through dialogue and interaction with users, we further analyze the content of reviews and the social influence of review authors to better help users. The results show that the dialogue mechanism proposed in this study has a good recommendation effect and can effectively improve user experience. Collapse

Semantic filters: MongoDB

Topics: recommender system social influence decision making user experience usability

Methods: experiment chatbot term frequency–inverse document frequency naïve bayes natural language processing
Developing a collaboration system for pancreatic cancer research: a clinical design science study
PDF
2023 | European Journal of Information Systems | Citations: 0
Authors: Rueckel, David; Krumay, Barbara; Dannerer, Ewald

Abstract: Great potential exists for the use of information systems (IS) in medical resear ... Expand

Abstract: Great potential exists for the use of information systems (IS) in medical research, as they already form the backbone of several long-term medical research projects. IS can potentially support practitioner-researchers (practitioners who conduct research in their areas of practice) by enabling collaboration, particularly when the number of cases is low and the treatment strategy is centralised. However, practitioner-researchers and academic researchers differ in their research approaches. In this clinical IS research effort, we designed an IS, together with a local hospital, for supporting research on pancreatic cancer by applying a design science research (DSR) approach. We also observed how DSR is accepted and used by practitioner-researchers in this context. Consequently, we not only developed an IS but also gained insights into the benefits of DSR in projects with heterogeneous participants, namely those from various fields with different experiences and requirements. The results show that DSR contributes to mutual understanding, transparency in the design process and long-term benefits for all parties involved, which was further confirmed by post-hoc interviews. Collapse

Semantic filters: MongoDB

Topics: usability user interface database system MongoDB systems development

Methods: design artifact qualitative interview design process design science field study
Towards solving ontological dissonance using network graphs

2023 | Americas Conference on Information Systems | Citations: 0
Authors: Stäbler, Maximilian; Köster, Frank; Schlueter-Langdon, Christoph

Abstract: Data Spaces are an emerging concept for the trusted implementation of data-base ... Expand

Abstract: Data Spaces are an emerging concept for the trusted implementation of data-based applications and business models, offering a high degree of flexibility and sovereignty to all stakeholders. As Data Spaces are currently emerging in different domains such as mobility, health or food, semantic interfaces need to be identified and implemented to ensure the technical interoperability of these Data Spaces. This paper consolidates data models from 13 different domains and analyzes the ontological dissonance of these domains. Using a network graph, central data models and ontology attributes are identified, while the semantic heterogeneity of these domains is described qualitatively. The research outlook describes how these results help to connect different Data Spaces across domains. Collapse

Semantic filters: MongoDB

Topics: Python database system MongoDB knowledge representation

Methods: ontological modelling data modeling graph analysis
Breakthroughs on Cross-Cutting Data Management, Data Analytics, and Applied Data Science
PDF
2021 | Information Systems Frontiers | Citations: 0
Authors: Chiusano, Silvia; Cerquitelli, Tania; Wrembel, Robert; Quercia, Daniele

Abstract: ... Expand

Abstract: Collapse

Semantic filters: MongoDB

Topics: mobile system internet of things Twitter MongoDB application programming interface

Methods: network analysis
Integrating Blockchain for Data Sharing and Collaboration Support in Scientific Ecosystem Platform
PDF
2021 | HICSS | Citations: 0
Authors: Coelho, Raiane; Braga, Regina; David, José Maria; Dantas, Mário; Stroele, Victor; Campos, Fernanda

Abstract: Nowadays, scientific experiments are conducted collaboratively. In collaborative ... Expand

Abstract: Nowadays, scientific experiments are conducted collaboratively. In collaborative scientific experiments, we must consider aspects such as interoperability, privacy, and trust in shared data to allow the reproducibility of the results. A critical aspect associated with a scientific process is its provenance information, which can be defined as the origin or lineage of the data that helps understand the scientific experiment results. Another concern when conducting collaborative experiments is confidentiality, considering that only authorized personnel can share or view results. In this paper, we propose BlockFlow, a blockchain-based architecture, to bring reliability to the collaborative research, considering the capture, storage, and analysis of provenance data related to a scientific ecosystem platform (E-SECO). Collapse

Semantic filters: MongoDB

Topics: Hyperledger blockchain application programming interface cloud computing covid 19

Methods: experiment literature study
TextBenDS: a Generic Textual Data Benchmark for Distributed Systems
PDF
2021 | Information Systems Frontiers | Citations: 0
Authors: Truică, Ciprian-Octavian; Apostol, Elena-Simona; Darmont, Jérôme; Assent, Ira

Abstract: Extracting top-k keywords and documents using weighting schemes are popular tech ... Expand

Abstract: Extracting top-k keywords and documents using weighting schemes are popular techniques employed in text mining and machine learning for different analysis and retrieval tasks. The weights are usually computed in the data preprocessing step, as they are costly to update and keep track of all the modifications performed on the dataset. Furthermore, calculation errors are introduced when analyzing only subsets of the dataset, i.e., wrong weighting are computed as weighting schemes use the number of documents for scoring keywords and documents. Therefore, in a Big Data context, it is crucial to lower the runtime of computing weighting schemes, without hindering the analysis process and the accuracy of the machine learning algorithms. To address this requirement for the task of computing top-k keywords and documents (which largely relies on weighting schemes), it is customary to design benchmarks that compare weighting schemes within various configurations of distributedframeworks and database management systems. Thus, we propose TextBenDS - a generic document-oriented benchmark for storing textual data and constructing weighting schemes. Our benchmark offers a generic data model designed with a multidimensional approach for storing text documents. We also propose using aggregation queries with various complexities and selectivities for constructing term weighting schemes, that are utilized in extracting top-k keywords and documents. We evaluate the computing performance of the queries on several distributed environments set within the Apache Hadoop ecosystem. Our experimental results provide interesting insights. As an example, MongoDB shows the best overall performance, while Spark’s execution time remains almost constant regardless of weighting schemes. Collapse

Semantic filters: MongoDB

Topics: information retrieval MongoDB database system distributed system MapReduce

Methods: term frequency–inverse document frequency Okapi BM25 experiment design science qualitative content analysis
Applying Multi-Criteria Decision-Making for the Selection of Big Data Technologies

2021 | Americas Conference on Information Systems | Citations: 0
Authors: Volk, Matthias; Staegemann, Daniel; Bischoff, Dennis; Turowski, Klaus

Abstract: For many years now big data presents itself as a technical starting point for a ... Expand

Abstract: For many years now big data presents itself as a technical starting point for a multitude of different trends, including data science, artificial intelligence, the internet of things, industry 4.0, and others. However, many decision makers are still challenged by the realization of related projects. One of the major problems arises from the multitude of existing technologies as well their selection and application. Due to that, in this paper, applying the design science research methodology, a comprehensive investigation about the application of multi-criteria decision-making (MCDM) methods is conducted. Apart from a structured literature review that seeks to identify relevant requirements for the technology selection, a conceptual model, as well as a prototypical implementation in the form of a decision support system, are presented. In the future, further MCDM approaches shall be tested and the system implemented in larger processes, including general sensemaking, system architecture modeling and rapid deployment. Collapse

Semantic filters: MongoDB

Topics: big data decision support decision support system Apache Hadoop electronic authentication

Methods: design artifact structured literature research experiment design science multiple criteria decision making
A Longitudinal Study of a Capstone Course

2020 | Americas Conference on Information Systems | Citations: 0
Authors: Gan, Benjamin Kok Siew; Ouh, Eng Lieh; LEE, Yin Yin Fiona

Abstract: This is a 7 years study on a capstone course completed by 1700+ students for 20 ... Expand

Abstract: This is a 7 years study on a capstone course completed by 1700+ students for 200+ organizations involving 300+ projects. Student teams deliver a system to solve real-world problems proposed by industry partners. We want to understand what independent variables influence student performance. We analyzed the deployment status of systems delivered, the type of organization/industry, the number of meetings and the technology used. Our results show some organization value proof of concept over fully deployed systems, student strengths are in Infocomm and Finance projects, the number of meetings is a weak correlation to performance and best performing projects are fully deployed on iOS using Microsoft technologies. Faculty can use these insights to focus on factors such as the type of industry projects and technology used. They may not be overly concern if student teams have fewer meetings or did not fully deployed their system, so long as they create value. Collapse

Semantic filters: MongoDB

Topics: MySQL database system iOS team productivity project management

Methods: survey parametric test Student's t-test nonparametric test design artifact

Page 1 of 3 Next

AIS11

Journals

Conferences

Semantic Filter

Found 29 articles

Cost-based Optimization of Multistore Query Plans

Navigating Workload Compatibility Between a Recommender System and a NoSQL Database: An Interactive Tutorial

A Chat-based personal recommendation mechanism with opinion intelligence

Developing a collaboration system for pancreatic cancer research: a clinical design science study

Towards solving ontological dissonance using network graphs

Breakthroughs on Cross-Cutting Data Management, Data Analytics, and Applied Data Science

Integrating Blockchain for Data Sharing and Collaboration Support in Scientific Ecosystem Platform

TextBenDS: a Generic Textual Data Benchmark for Distributed Systems

Applying Multi-Criteria Decision-Making for the Selection of Big Data Technologies

A Longitudinal Study of a Capstone Course