Showing papers in "Information Systems in 2020"

TL;DR: Different topic modeling approaches capable of dealing with correlation between topics, the changes of topics over time, as well as the ability to handle short texts such as encountered in social media or sparse text data are presented.

TL;DR: This work proposes a metric to measure the community-diversified influence and addresses a series of computational challenges that have been verified through extensive experimental studies on five real-world social network datasets.

TL;DR: The results showed that the proposed methods significantly improved the efficiency and performance of certain classifiers, such as k-Nearest Neighbor, Support Vector Machine, and neural networks.

TL;DR: The findings of this review highlighted SOA Governance, SOA Strategy, Financial Issues and Costs, and Education and Training as the most significant factors of SOA adoption and implementation.

TL;DR: In this paper, the authors present a detailed analysis of 63 approaches for the development of IoT platforms and propose an evaluation framework as a cornerstone to highlight the characteristics, strengths, and weaknesses of these approaches.

TL;DR: A taxonomy of smart city features, dimensions, actions and goals, and, according to these variables, the existing literature on recommender systems is surveyed, to show current opportunities and challenges where personalized recommendations could be exploited as solutions for citizens, firms and public administrations.

TL;DR: By its principles, GDPR is synthesised as a concept lattice, that is, a formal summary of the regulation, featuring 144372 records — its uses are manifold and the lattice captures so-called attribute implications, the implicit logical relations across theregulation, and their intensity.

TL;DR: JedAI is an open-source system that puts together a series of state-of-the-art ER techniques that have been proposed and examined independently, targeting parts of the ER end-to-end pipeline, a unique approach as no other ER tool brings together so many established techniques.

TL;DR: Background and advanced basketball metrics used in National Basketball Association (NBA) and Euroleague games are reviewed to benchmark existing performance analytics used in the literature for evaluating teams and players.

TL;DR: This paper reports on a Systematic Literature Review aimed to analyze published standard modeling language specifications and reveals heterogeneity in: (i) the modeling language concepts being specified, and (ii) the techniques being employed for the specification of these concepts.

TL;DR: This work studies closely the experimental methodology used in prior work and their generalizability to other datasets, and designs some baseline approaches to perform cross-lingual experiments, using English and Spanish datasets.

TL;DR: This paper proposes a formal data model for JSON documents and defines a lightweight query language allowing us to navigate through JSON documents, study the complexity of basic computational tasks associated with this language, and compare its expressive power with practical languages for managing JSON data.

TL;DR: This work combined existing concepts and ontologies to define a “Hybrid Business Process Representation” (HBPR), and conducted a Systematic Literature Review to identify and investigate the characteristics of HBPRs combining imperative and declarative languages or artifacts.

TL;DR: This paper proposes a novel anomaly detection approach based on association rule mining that fosters the explanation of anomalies and the estimation of their severity and is able to deal with process change and flexible executions which potentially lead to false positives.

TL;DR: A comprehensive presentation of the architecture of the Vadalog system and showing how the techniques work together to provide a full-fledged KGMS is presented, including a new series of experiments designed to shed light on architectural choices and alternatives.

TL;DR: The paper presents and compares two approaches to the problem of discovering constraints that involve two activities of the process such that each of these two activities is associated with a condition that must hold when the activity occurs.

TL;DR: AdaptiveBPM proposes a modeling methodology to semantically capture the business interests, enterprise environment and process space in accordance with the agent-oriented software engineering paradigm, and is shown that agileBPM is the most comprehensive knowledge-intensive process management solution.

TL;DR: It is shown from a trust model for consortium collaborative networks that current consortium blockchain systems provide limited support for decentralized data access control (DDAC), and a general framework is proposed to help inexperienced users determine appropriate strategies under different application scenarios.

TL;DR: A review on graph-based methods (types of graphs and search algorithms) as well as a detailed discussion on the applicability of search algorithms (with exact or approximate answers) in each graph type and an experimental evaluation of representative graphs implemented in a common platform.

TL;DR: A novel 3-PAKE protocol for HWSN applications, with two extensions for additional security features, that is provably secure, efficient and flexible is proposed.

TL;DR: This work contributes a categorization of ISC as well as four discovery algorithms for ISC candidates from process execution logs that contribute to a digitalized ISC and compliance management.

TL;DR: A Significance-Based Trust-Aware Recommendation (SBTAR) approach, which uses a new trust measure based on the concept of item significance, which can adapt to dynamic changes in user preferences.

TL;DR: Grosman et al. as mentioned in this paper developed a web-based text annotation tool to facilitate and manage the process of text annotation, which includes not only the key features of current mainstream annotation systems but also other features necessary to improve the curation process, such as the inter-annotator agreement, self-agreement and annotation log visualization, for annotation quality control.

TL;DR: This paper provides a detailed taxonomy of attacks on RSA cryptosystems and discusses their strengths and weaknesses while attacking different algorithmic implementations of RSA, and provides a classification of these attacks based on the source of information leakage.

TL;DR: A new approach which takes the quality of documents into account in scoring step and can improve the MAP measure up to 46% on average, in comparison with the state-of-the-art expert finding approach.

TL;DR: Research works in the fields of query suggestion, particularly query auto-completion have been studied with special attention to customization, finding that the research works employing context or time as sophisticated features for customization are more than those using location or demographic features.

TL;DR: It is revealed that misfit of information systems software (closely followed by lack of top management support and unsuccessful monitoring and measurement) has the greatest impact on the failure of Information systems in the public universities of Iran.

TL;DR: The Green Man is a deictic trans-historical figure and motif shared by both interconnected canons and folklores, as well as those seemingly disparate as discussed by the authors, and it has manifold associations to religiously significant personalities like St. George, Elijah, Gilgamesh, Buddha, Christ, and Melchizedek.

TL;DR: Experimental results on various synthetic and real-world datasets demonstrate the obvious superiority of CutPC compared with k-means, DBSCAN, DPC, SC, and DCore.

TL;DR: In this article, the authors leverage previous work on probabilistic models to develop a Dynamic Bayesian Network technique to model context attributes that have either a cause or effect relationship towards the event.