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

Metaverse Knowledge Graph Construction: An Unsupervised Relation Extraction Approach based on Semantic Mining

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Li, Litao; Xu, Ruiyun; Zhao, J. Leon

Abstract: Metaverse has gained widespread attention in both academia and industry. As a r ... Expand

Abstract: Metaverse has gained widespread attention in both academia and industry. As a result, many new concepts, methodologies, and applications are emerging in recent years. Constructing a Metaverse knowledge graph can help with knowledge management and facilitate various intelligent tasks such as recommendations, information retrieval, and chatbots in this emerging field. However, existing knowledge graph construction approaches are not directly applicable in the Metaverse domain due to a lack of labeled dataset, making existing supervised relation extraction approaches impracticable. In this study, we develop a novel graph construction framework by integrating the deep learning approach (i.e., BERT-BiLSTM-CRF) with an unsupervised relation extraction approach based on semantic mining. The framework we propose in this paper can automatically construct knowledge graphs while significantly reducing labeling efforts. Further, we plan to implement the proposed framework on a Metaverse corpus to construct a Metaverse knowledge graph. To test our approach, we will employ an expert-survey method to evaluate the quality of triple sets. Collapse

Topics: virtual reality knowledge graph mobile application blog artificial intelligence

Methods: BERT survey word2vec deep learning named entity recognition

An Approach to Extracting Topic-guided Views from the Sources of a Data Lake

2021 | Information Systems Frontiers | Citations: 0

Authors: Diamantini, Claudia; Lo Giudice, Paolo; Potena, Domenico; Storti, Emanuele; Ursino, Domenico

Abstract: In the last years, data lakes are emerging as an effective and an efficient supp ... Expand

Abstract: In the last years, data lakes are emerging as an effective and an efficient support for information and knowledge extraction from a huge amount of highly heterogeneous and quickly changing data sources. Data lake management requires the definition of new techniques, very different from the ones adopted for data warehouses in the past. In this scenario, one of the most challenging issues to address consists in the extraction of topic-guided (i.e., thematic) views from the (very heterogeneous and often unstructured) sources of a data lake. In this paper, we propose a new network-based model to uniformly represent structured, semi-structured and unstructured sources of a data lake. Then, we present a new approach to, at least partially, “structuring” unstructured data. Finally, we define a technique to extract topic-guided views from the sources of a data lake, based on similarity and other semantic relationships among source metadata. Collapse

Topics: data lake knowledge representation knowledge graph Wikipedia database system

Methods: computational algorithm experiment DBpedia cluster analysis machine learning

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

Teaching NoSQL Data Models: A Tutorial

2021 | Americas Conference on Information Systems | Citations: 0

Authors: Greiner, Martina

Abstract: This tutorial discusses the four most popular categories of NoSQL databases: ke ... Expand

Abstract: This tutorial discusses the four most popular categories of NoSQL databases: key-value databases, document databases, graph databases, and wide column databases. For each NoSQL database type, we explain differences to traditional relational database management systems, how data is organized using Airbnb as an example, and benefits and drawbacks. Collapse

Topics: Airbnb nosql database database system relational database Cassandra

Methods: data modeling conceptual modelling design science entity relationship modeling

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

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

An Automatic Ontology Generation Framework with An Organizational Perspective

2020 | HICSS | Citations: 0

Authors: Elnagar, Samaa; Yoon, Victoria; Thomas, Manoj A

Abstract: Ontologies have been known for their powerful semantic representation of knowled ... Expand

Abstract: Ontologies have been known for their powerful semantic representation of knowledge. However, ontologies cannot automatically evolve to reflect updates that occur in respective domains. To address this limitation, researchers have called for automatic ontology generation from unstructured text corpus. Unfortunately, systems that aim to generate ontologies from unstructured text corpus are domain-specific and require manual intervention. In addition, they suffer from uncertainty in creating concept linkages and difficulty in finding axioms for the same concept. Knowledge Graphs (KGs) has emerged as a powerful model for the dynamic representation of knowledge. However, KGs have many quality limitations and need extensive refinement. This research aims to develop a novel domain-independent automatic ontology generation framework that converts unstructured text corpus into domain consistent ontological form. The framework generates KGs from unstructured text corpus as well as refine and correct them to be consistent with domain ontologies. The power of the proposed automatically generated ontology is that it integrates the dynamic features of KGs and the quality features of ontologies. Collapse

Topics: knowledge representation web page predicate logic knowledge graph social media

Methods: ontological modelling computational algorithm domain ontology DOLCE ontology WordNet

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