Is There More Than Pokémon Go? -Exploring the State of Research on Causal Modeling in the Field of Augmented Reality

2023 | HICSS | Citations: 0

Authors: Bräker, J.; Semmann, M.

Abstract: The paper explores how scholars apply causal modeling to gain an understanding ... Expand

Abstract: The paper explores how scholars apply causal modeling to gain an understanding of augmented reality as innovative technology and its potential for application. To do so, we conducted a structured literature review and applied a graph database-driven approach to analyze how scholars research augmented reality. Such an approach enables in-depth analysis of the body of knowledge that is not accessible in traditional ways of exploring literature. The results help to understand where we as a community stand and how directions for future research can help reshape the understanding of augmented reality and its application. Collapse

Topics: augmented reality smart device graph database perceived usefulness Neo4j

Methods: structural equation modeling structured literature research literature study literature sample synthesis

Theories: technology acceptance model cue utilization theory extended unified theory of acceptance and use of technology

A New Approach for Mining Correlated Frequent Subgraphs

2022 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Chowdhury, Mohammad Ehsan Shahmi; Ahmed, Chowdhury Farhan; Leung, Carson K.

Abstract: Nowadays graphical datasets are having a vast amount of applications. As a resul ... Expand

Abstract: Nowadays graphical datasets are having a vast amount of applications. As a result, graph mining—mining graph datasets to extract frequent subgraphs—has proven to be crucial in numerous aspects. It is important to perform correlation analysis among the subparts (i.e., elements) of the frequent subgraphs generated using graph mining to observe interesting information. However, the majority of existing works focuses on complexities in dealing with graphical structures, and not much work aims to perform correlation analysis. For instance, a previous work realized in this regard, operated with a very naive raw approach to fulfill the objective, but dealt only on a small subset of the problem. Hence, in this article, a new measure is proposed to aid in the analysis for large subgraphs, mined from various types of graph transactions in the dataset. These subgraphs are immense in terms of their structural composition, and thus parallel the entire set of graphs in real-world. A complete framework for discovering the relations among parts of a frequent subgraph is proposed using our new method. Evaluation results show the usefulness and accuracy of the newly defined measure on real-life graphical datasets. Collapse

Topics: graph database database system Microsoft Windows website programming language

Methods: computational algorithm experiment literature study nonparametric test Mann Whitney U test

TopoGraph: an End-To-End Framework to Build and Analyze Graph Cubes

2021 | Information Systems Frontiers | Citations: 0

Authors: Ghrab, Amine; Romero, Oscar; Skhiri, Sabri; Zimányi, Esteban

Abstract: Graphs are a fundamental structure that provides an intuitive abstraction for mo ... Expand

Abstract: Graphs are a fundamental structure that provides an intuitive abstraction for modeling and analyzing complex and highly interconnected data. Given the potential complexity of such data, some approaches proposed extending decision-support systems with multidimensional analysis capabilities over graphs. In this paper, we introduce TopoGraph, an end-to-end framwork for building and analyzing graph cubes. TopoGraph extends the existing graph cube models by defining new types of dimensions and measures and organizing them within a multidimensional space that guarantees multidimensional integrity constraints. This results in defining three new types of graph cubes: property graph cubes, topological graph cubes, and graph-structured cubes. Afterwards, we define the algebraic OLAP operations for such novel cubes. We implement and experimentally validate TopoGraph with different types of real-world datasets. Collapse

Topics: online analytical processing Twitter Neo4j application programming interface social network

Methods: computational algorithm multidimensional modeling experiment design artifact cluster analysis

Combining Graph Exploration and Fragmentation for Scalable RDF Query Processing

2021 | Information Systems Frontiers | Citations: 0

Authors: Khelil, Abdallah; Mesmoudi, Amin; Galicia, Jorge; Bellatreche, Ladjel; Hacid, Mohand-Saïd; Coquery, Emmanuel

Abstract: The flexibility offered by the Resource Description Framework (RDF) has led it t ... Expand

Abstract: The flexibility offered by the Resource Description Framework (RDF) has led it to become a very popular standard for representing data with an undefined or variable schema using the concept of triples. Its success has resulted in many large scale multidisciplinary datasets, that have prompted the development of efficient RDF processing systems. Current approaches can be distinguished into two groups: the first, adopting the relational model storing the triples in tables, and the second creating data structures that model RDF data as a graph. The strategies of the first group are more easily scalable since they apply optimization strategies from the relational model like indexing and fragmentation. However, these approaches suffer many overheads when dealing with complex queries (e.g. compounded SPARQL graphs involving filters) persistent in existing applications. On the other hand, graph-based systems that use more complex data structures fail to efficiently manage the main memory and are not scalable in computer hardware with limited resources. In this paper, we propose a novel approach to perform queries (Basic Graph Patterns, Wildcards, Aggregations and Sorting) on RDF data. We propose to combine both RDF graph exploration with physical fragmentation of triples. In this work, we describe our graph-based storage and query evaluation models. Then, we detail the architecture of our system and we largely explain the strategy, based in the Volcano execution model, used to manage the main memory at query runtime. We conducted extensive experiments on synthetic and real datasets to evaluate the efficiency of our proposal. We compared our performance with a relational-based (Virtuoso), a graph-based (gStore) and an intensive-indexing (RDF-3X) approach. According to our evaluation, our system offers the best compromise between efficient query processing and scalability. Collapse

Topics: computer hardware Neo4j graph database structured query language database system

Methods: experiment computational algorithm leading question literature study

Literature Reviewing: Addressing the Jingle and Jangle Fallacies and Jungle Conundrum Using Graph Theory and NLP

2021 | International Conference on Information Systems | Citations: 0

Authors: Song, Yuanyuan; Watson, Richard T.; Zhao, Xia

Abstract: Scientific advancements in all fields, including IS, are built on previous acco ... Expand

Abstract: Scientific advancements in all fields, including IS, are built on previous accomplishment. Identifying similar causal models is critical for synthesizing research. However, the growing knowledge repository and inconsistencies in existing literature (i.e., jingle and jangle fallacies) challenge humans' bounded rationality. Humans need supporting information systems to make a jungle of causal models amenable to analysis. This paper proposes using graph theory and natural language processing (NLP) methods to analyze knowledge networks and report similarity scores for causal models. This method builds on the first phase of the Theory Research Exchange (T-Rex) project, in which guidance on digitizing the core knowledge in publications is established. Digitizing core knowledge will provide an efficiency gain as illustrated in this paper and be a significant step forward for the knowledge economy. Collapse

Topics: privacy database system graph database internet technology information privacy concern

Methods: computational algorithm natural language processing survey literature study experiment

Theories: graph theory

Follow the money: Revealing risky nodes in a Ransomware-Bitcoin network

2021 | HICSS | Citations: 0

Authors: Turner, Adam; Mccombie, Stephen; Uhlmann, Allon

Abstract: This paper demonstrates the use of network analysis to identify core nodes assoc ... Expand

Abstract: This paper demonstrates the use of network analysis to identify core nodes associated with ransomware attacks in cryptocurrency transaction networks. The method helps trace the cyber entities involved in cryptocurrency attacks and supports intelligence efforts to identify and disrupt cryptocurrency networks. Collapse

Topics: ransomware Bitcoin open source application programming interface cryptocurrency

Methods: computational algorithm machine learning k-means clustering data transformation principal component analysis

Maintenance of Enterprise Architecture Models

2021 | Business & Information Systems Engineering | Citations: 1

Authors: Silva, Nuno; Sousa, Pedro; Mira da Silva, Miguel

Abstract: Enterprise architecture (EA) models are tools of analysis, communication, and su ... Expand

Abstract: Enterprise architecture (EA) models are tools of analysis, communication, and support towards enterprise transformation. These models need a suitable maintenance process to support comprehensive knowledge of the enterprise’s structure and dynamics. This study aims to identify and discuss the existing approaches to EA model maintenance published in the scientific literature. A systematic literature review was employed as the research method. A keyword-based search in six databases identified a total of 4495 papers in which 31 primary studies were included. A total of nine categories of EA model maintenance approaches were identified from both information systems and enterprise engineering fields of research. The increasing amount of research in EA model maintenance suggests that the topic still presents opportunities for research contributions. This study also proposes future lines of research according to the results identified in the theoretical corpus. Collapse

Topics: access control enterprise architecture database system data management system support

Methods: case study computational algorithm literature sample survey literature study

A new emergency decision support system: the automatic interpretation and contextualisation of events to model a crisis situation in real-time

2020 | Decision Support Systems | Citations: 0

Authors: Fertier, Audrey; Barthe-Delanoë, Anne-Marie; Montarnal, Aurélie; Truptil, Sébastien; Bénaben, Frédérick

Abstract: This paper studies, designs and implements a new type of emergency decision supp ... Expand

Abstract: This paper studies, designs and implements a new type of emergency decision support system that aims to improve the decision-making of emergency managers in crisis situations by connecting them to new, multiple data sources. The system combines event-driven and model-driven architectures and is dedicated to crisis cells. After its implementation, the system is evaluated using a realistic crisis scenario, in terms of its user interfaces, its ability to interpret data in real time and its ability to manage the 4Vs of Big Data. The input events correspond to traffic measurements, water levels, water flows, water predictions and flow predictions made available by French official services. The main contributions of this study are: (i) the connection between a complex event processing engine and a graph database containing the model of the crisis situation and (ii) the continuous updating of a common operational picture for the benefit of emergency managers. This study could be used as a framework for future research works on decision support systems facing complex, evolving situations. Collapse

Topics: decision support system complex event processing database system graph database Neo4j

Methods: design science metamodel case study literature study ontological modelling

Efficient querying of multidimensional RDF data with aggregates: Comparing NoSQL, RDF and relational data stores

2020 | International Journal of Information Management | Citations: 0

Authors: Ravat, Franck; Song, Jiefu; Teste, Olivier; Trojahn, Cassia

Abstract: This paper proposes an approach to tackle the problem of querying large volume o ... Expand

Abstract: This paper proposes an approach to tackle the problem of querying large volume of statistical RDF data. Our approach relies on pre-aggregation strategies to better manage the analysis of this kind of data. Specifically, we define a conceptual model to represent original RDF data with aggregates in a multidimensional structure. A set of translations rules for converting a well-known multidimensional RDF modelling vocabulary into the proposed conceptual model is then proposed. We implement the conceptual model in six different data stores: two RDF triple stores (Jena TDB and Virtuoso), one graph-oriented NoSQL database (Neo4j), one column-oriented data store (Cassandra), and two relational databases (MySQL and PostGreSQL). We compare the querying performance, with and without aggregates, in these data stores. Experimental results, on real-world datasets containing 81.92 million triplets, show that pre-aggregation allows for reducing query runtime in all data stores. Neo4j NoSQL and relational databases with aggregates outperform triple stores speeding up to 99% query runtime. Collapse

Topics: Neo4j Cassandra relational database nosql database MySQL

Methods: experiment conceptual modelling computational algorithm multidimensional modeling optimization model

Modeling Historical Social Networks Databases

2019 | HICSS | Citations: 0

Authors: Akoka, Jacky; Comyn, Isabelle; Lamassé, Stéphane

Abstract: Historical social networks are analyzed using prosopographical methods. Prosopog ... Expand

Abstract: Historical social networks are analyzed using prosopographical methods. Prosopography is a branch of historical research that focuses on the identification of social networks that appear in historical sources. It aims to represent and to interpret historical data, sourced from texts. Conceptual modeling imparts the capability to process these large data sets. This paper outlines a conceptual approach to designing a prosopographical database encompassing uncertainty. Our contribution is threefold: i) a generic certaintybased prosopographical conceptual model; ii) two meta-models with a mapping between them; iii) an illustrative example generating a customized prosopographical relational model. Unlike past approaches, our design process helps us to integrate disparate points of view as expressed in the prosopography community. We apply our approach to the prosopographical database Studium Parisiense dedicated to members of Paris schools and university between the twelfth and sixteenth centuries. This instantiation validates the usefulness of our approach. Collapse

Topics: database system relational database social network IT career extensible markup language

Methods: conceptual modelling design science metamodel entity relationship modeling design artifact