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  • Knowledge-guided unsupervised rhetorical parsing for text summarization
    Inform. Syst. (IF 2.466) Pub Date : 2020-08-03
    Shengluan Hou; Ruqian Lu

    Automatic text summarization (ATS) has recently achieved impressive performance thanks to recent advances in deep learning and the availability of large-scale corpora. However, there is still no guarantee that the generated summaries are grammatical, concise, and convey all salient information as the original documents have. To make the summarization results more faithful, this paper presents an unsupervised

  • Every apprentice needs a master: Feedback-based effectiveness improvements for process model matching
    Inform. Syst. (IF 2.466) Pub Date : 2020-08-04
    Christopher Klinkmüller; Ingo Weber

    Process models are a central element of modern business process management technology. When adopting such technology, organizations inevitably establish process model collections which, depending on the degree of adoption, can reach sizes of thousands of models. Process model matching techniques are intended to assist experts in the management of such large collections, e.g., in querying the collections

  • XChange: A semantic diff approach for XML documents
    Inform. Syst. (IF 2.466) Pub Date : 2020-08-01
    Alessandreia Oliveira; Troy Kohwalter; Marcos Kalinowski; Leonardo Murta; Vanessa Braganholo

    XML documents are extensively used in several applications and evolve over time. Identifying the semantics of these changes becomes a fundamental process to understand their evolution. Existing approaches related to understanding changes (diff) in XML documents focus only on syntactic changes. These approaches compare XML documents based on their structure, without considering the associated semantics

  • DimensionSlice: A main-memory data layout for fast scans of multidimensional data
    Inform. Syst. (IF 2.466) Pub Date : 2020-07-25
    Ilhyun Suh; Yon Dohn Chung

    Multidimensional data are exploited in many application areas such as scientific data analysis, business intelligence, and geographic information systems. One of the most frequent operations applied to such multidimensional data is the selection of a subspace of the given multidimensional space, which involves predicate evaluation on multiple dimensions. Existing main-memory data layouts optimized

  • Privacy-aware data cleaning-as-a-service
    Inform. Syst. (IF 2.466) Pub Date : 2020-07-31
    Yu Huang; Mostafa Milani; Fei Chiang

    Data cleaning is a pervasive problem for organizations as they try to reap value from their data. Recent advances in networking and cloud computing technology have fueled a new computing paradigm called Database-as-a-Service, where data management tasks are outsourced to large service providers. In this paper, we consider a Data Cleaning-as-a-Service model that allows a client to interact with a data

  • Exploiting semantic relationships for unsupervised expansion of sentiment lexicons
    Inform. Syst. (IF 2.466) Pub Date : 2020-07-29
    Felipe Viegas; Mário S. Alvim; Sérgio Canuto; Thierson Rosa; Marcos André Gonçalves; Leonardo Rocha

    The literature in sentiment analysis has widely assumed that semantic relationships between words cannot be effectively exploited to produce satisfactory sentiment lexicon expansions. This assumption stems from the fact that words considered to be “close” in a semantic space (e.g., word embeddings) may present completely opposite polarities, which might suggest that sentiment information in such spaces

  • Fragments of bag relational algebra: Expressiveness and certain answers
    Inform. Syst. (IF 2.466) Pub Date : 2020-07-22
    Marco Console; Paolo Guagliardo; Leonid Libkin

    While all relational database systems are based on the bag data model, much of theoretical research still views relations as sets. Recent attempts to provide theoretical foundations for modern data management problems under the bag semantics concentrated on applications that need to deal with incomplete relations, i.e., relations populated by constants and nulls. Our goal is to provide a complete characterization

  • Relevance- and interface-driven clustering for visual information retrieval
    Inform. Syst. (IF 2.466) Pub Date : 2020-07-13
    Mohamed Reda Bouadjenek; Scott Sanner; Yihao Du

    Search results of spatio-temporal data are often displayed on a map, but when the number of matching search results is large, it can be time-consuming to individually examine all results, even when using methods such as filtered search to narrow the content focus. This suggests the need to aggregate results via a clustering method. However, standard unsupervised clustering algorithms like K-means (i)

  • Providing accurate answers to OLAP queries based on standardized moments of data cubes
    Inform. Syst. (IF 2.466) Pub Date : 2020-07-08
    Elaheh Pourabbas

    In this paper, we focus on the problem of providing accurate estimates to a target data cube from sets of source data cubes, which share the same summary measures. We investigate the acyclic and cyclic schemas of data sources and show that the more accurate target data cube can be computed on the basis of third and fourth standardized moments (i.e., skewness and kurtosis, respectively) of the source

  • Decentralized data access control over consortium blockchains
    Inform. Syst. (IF 2.466) Pub Date : 2020-07-09
    Yaoliang Chen; Shi Chen; Jiao Liang; Lance Warren Feagan; Weili Han; Sheng Huang; X. Sean Wang

    Blockchain is an emerging data management technology that enables people in a collaborative network to establish trusted connections with the other participants. Recently consortium blockchains have raised interest in a broader blockchain technology discussion. Instead of a fully public, autonomous network, consortium blockchain supports a network where participants can be limited to a subset of users

  • Processing tweets for cybersecurity threat awareness
    Inform. Syst. (IF 2.466) Pub Date : 2020-07-04
    Fernando Alves; Aurélien Bettini; Pedro M. Ferreira; Alysson Bessani

    Receiving timely and relevant security information is crucial for maintaining a high-security level on an IT infrastructure. This information can be extracted from Open Source Intelligence published daily by users, security organisations, and researchers. In particular, Twitter has become an information hub for obtaining cutting-edge information about many subjects, including cybersecurity. This work

  • A review of topic modeling methods
    Inform. Syst. (IF 2.466) Pub Date : 2020-06-18
    Ike Vayansky; Sathish A.P. Kumar

    Topic modeling is a popular analytical tool for evaluating data. Numerous methods of topic modeling have been developed which consider many kinds of relationships and restrictions within datasets; however, these methods are not frequently employed. Instead many researchers gravitate to Latent Dirichlet Analysis, which although flexible and adaptive, is not always suited for modeling more complex data

  • Hate speech detection is not as easy as you may think: A closer look at model validation (extended version)
    Inform. Syst. (IF 2.466) Pub Date : 2020-06-30
    Aymé Arango; Jorge Pérez; Barbara Poblete

    Hate speech is an important problem that is seriously affecting the dynamics and usefulness of online social communities. Large scale social platforms are currently investing important resources into automatically detecting and classifying hateful content, without much success. On the other hand, the results reported by state-of-the-art systems indicate that supervised approaches achieve almost perfect

  • Scenario-based process querying for compliance, reuse, and standardization
    Inform. Syst. (IF 2.466) Pub Date : 2020-05-27
    Artem Polyvyanyy; Anastasiia Pika; Arthur H.M. ter Hofstede

    Process models constitute valuable artifacts for organizations. A process model formally captures the way an organization works internally and interacts with its customers and partners. Over time, more models may be created as business practices evolve (leading to different versions of models) or an organization expands, e.g., through mergers or acquisitions. It is not uncommon for large organizations

  • Using a modelling language to describe the quality of life goals of people living with dementia
    Inform. Syst. (IF 2.466) Pub Date : 2020-06-15
    James Lockerbie; Neil Maiden

    Although now well established, our information systems engineering theories and methods are applied only rarely in disciplines beyond systems development. This paper reports the application of the i* goal modelling language to describe the types of and relationships between quality of life goals of people living with dementia. Published social care frameworks to manage and improve the lives of people

  • Comprehending 3D and 4D ontology-driven conceptual models: An empirical study
    Inform. Syst. (IF 2.466) Pub Date : 2020-06-03
    Michaël Verdonck; Frederik Gailly; Sergio de Cesare

    This paper presents an empirical study that investigates the extent to which the pragmatic quality of ontology-driven models is influenced by the choice of a particular ontology, given a certain understanding of that ontology. To this end, we analyzed previous research efforts and distilled three hypotheses based on different metaphysical characteristics. An experiment based on two foundational ontologies

  • Continuous outlier mining of streaming data in flink
    Inform. Syst. (IF 2.466) Pub Date : 2020-05-29
    Theodoros Toliopoulos; Anastasios Gounaris; Kostas Tsichlas; Apostolos Papadopoulos; Sandra Sampaio

    In this work, we focus on distance-based outliers in a metric space, where the status of an entity as to whether it is an outlier is based on the number of other entities in its neighborhood. In recent years, several solutions have tackled the problem of distance-based outliers in data streams, where outliers must be mined continuously as new elements become available. An interesting research problem

  • Three-dimensional Entity Resolution with JedAI
    Inform. Syst. (IF 2.466) Pub Date : 2020-05-27
    George Papadakis; George Mandilaras; Luca Gagliardelli; Giovanni Simonini; Emmanouil Thanos; George Giannakopoulos; Sonia Bergamaschi; Themis Palpanas; Manolis Koubarakis

    Entity Resolution (ER) is the task of detecting different entity profiles that describe the same real-world objects. To facilitate its execution, we have developed JedAI, 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. This is a unique approach, as no other ER tool

  • Sports analytics — Evaluation of basketball players and team performance
    Inform. Syst. (IF 2.466) Pub Date : 2020-05-23
    Vangelis Sarlis; Christos Tjortjis

    Given the recent trend in Data Science (DS) and Sports Analytics, an opportunity has arisen for utilizing Machine Learning (ML) and Data Mining (DM) techniques in sports. This paper reviews background and advanced basketball metrics used in National Basketball Association (NBA) and Euroleague games. The purpose of this paper is to benchmark existing performance analytics used in the literature for

  • Scalable alignment of process models and event logs: An approach based on automata and S-components
    Inform. Syst. (IF 2.466) Pub Date : 2020-05-22
    Daniel Reißner; Abel Armas-Cervantes; Raffaele Conforti; Marlon Dumas; Dirk Fahland; Marcello La Rosa

    Given a model of the expected behavior of a business process and given an event log recording its observed behavior, the problem of business process conformance checking is that of identifying and describing the differences between the process model and the event log. A desirable feature of a conformance checking technique is that it should identify a minimal yet complete set of differences. Existing

  • Eras: Improving the quality control in the annotation process for Natural Language Processing tasks
    Inform. Syst. (IF 2.466) Pub Date : 2020-05-21
    Jonatas S. Grosman; Pedro H.T. Furtado; Ariane M.B. Rodrigues; Guilherme G. Schardong; Simone D.J. Barbosa; Hélio C.V. Lopes

    The increasing amount of valuable, unstructured textual information poses a major challenge to extract value from those texts. We need to use NLP (Natural Language Processing) techniques, most of which rely on manually annotating a large corpus of text for its development and evaluation. Creating a large annotated corpus is laborious and requires suitable computational support. There are many annotation

  • DMAKit: A user-friendly web platform for bringing state-of-the-art data analysis techniques to non-specific users
    Inform. Syst. (IF 2.466) Pub Date : 2020-05-16
    David Medina-Ortiz; Sebastián Contreras; Cristofer Quiroz; Juan A. Asenjo; Álvaro Olivera-Nappa
  • Vadalog: A modern architecture for automated reasoning with large knowledge graphs
    Inform. Syst. (IF 2.466) Pub Date : 2020-05-11
    Luigi Bellomarini; Davide Benedetto; Georg Gottlob; Emanuel Sallinger

    The introduction of novel Datalog +/- fragments with good theoretical properties, together with the growing use of enterprise knowledge graphs motivated the development of Vadalog, a knowledge graph management system developed at the University of Oxford. It adopts Warded Datalog +/- as the core of its language for knowledge representation and reasoning, which exhibits a very good tradeoff between

  • Process discovery with context-aware process trees
    Inform. Syst. (IF 2.466) Pub Date : 2020-05-08
    Roee Shraga; Avigdor Gal; Dafna Schumacher; Arik Senderovich; Matthias Weidlich

    Discovery plays a key role in data-driven analysis of business processes. The vast majority of contemporary discovery algorithms aims at the identification of control-flow constructs. The increase in data richness, however, enables discovery that incorporates the context of process execution beyond the control-flow perspective. A “control-flow first” approach, where context data serves for refinement

  • SchemaDecrypt++: Parallel on-line Versioned Schema Inference for Large Semantic Web Data sources
    Inform. Syst. (IF 2.466) Pub Date : 2020-05-06
    Kenza Kellou-Menouer; Zoubida Kedad

    A growing number of linked data sources are published on the Web. They form a single huge data space referred to as the Web of data. These data sources contain both the data and the schema describing them, but the data is not constrained by this schema. Indeed, two instances of the same class may be described by different properties. This flexibility for describing the data eases their evolution, but

  • Explaining data with descriptions
    Inform. Syst. (IF 2.466) Pub Date : 2020-05-04
    Matteo Paganelli; Paolo Sottovia; Antonio Maccioni; Matteo Interlandi; Francesco Guerra

    With the advent of Big Data, it is impossible for a human user to properly inspect and understand data at a glance. In this paper, we introduce the problem of generating data descriptions: a set of compact, readable and insightful formulas of boolean predicates that represents a set of data records. Unfortunately, finding the best description for a dataset is both NP-hard and task-specific. Therefore

  • Recommender systems for smart cities
    Inform. Syst. (IF 2.466) Pub Date : 2020-04-28
    Lara Quijano-Sánchez; Iván Cantador; María E. Cortés-Cediel; Olga Gil

    Among other conceptualizations, smart cities have been defined as functional urban areas articulated by the use of Information and Communication Technologies (ICT) and modern infrastructures to face city problems in efficient and sustainable ways. Within ICT, recommender systems are strong tools that filter relevant information, upgrading the relations between stakeholders in the polity and civil society

  • Evaluation of factors contributing to the failure of information systems in public universities: The case of Iran
    Inform. Syst. (IF 2.466) Pub Date : 2020-04-24
    Siamak Kheybari; Fariba Mahdi Rezaie; S. Ali Naji; Mahsa Javdanmehr; Jafar Rezaei

    In this paper, we evaluate the reasons for the failure of information systems in public universities. To that end, we start by presenting a hierarchical structure of criteria after reviewing related studies, and dividing the criteria into the categories of project management, organizational management, human-related, organizational and technical. To assess the weight of the criteria in the proposed

  • Automatic latent street type discovery from web open data
    Inform. Syst. (IF 2.466) Pub Date : 2020-04-24
    Yihong Zhang; Panote Siriaraya; Yukiko Kawai; Adam Jatowt

    Street categorization is an important topic in urban planning and in various applications such as routing and environment monitoring. Typically streets are classified as commercial, residential, and industrial. However, such broad categorization is insufficient to capture the rich properties a street may possess, and often cannot be used for specific applications. Previous works have proposed several

  • Community-diversified influence maximization in social networks
    Inform. Syst. (IF 2.466) Pub Date : 2020-03-26
    Jianxin Li; Taotao Cai; Ke Deng; Xinjue Wang; Timos Sellis; Feng Xia

    To meet the requirement of social influence analytics in various applications, the problem of influence maximization has been studied in recent years. The aim is to find a limited number of nodes (i.e., users) which can activate (i.e. influence) the maximum number of nodes in social networks. However, the community diversity of influenced users is largely ignored even though it has unique value in

  • Efficient processing of reverse nearest neighborhood queries in spatial databases
    Inform. Syst. (IF 2.466) Pub Date : 2020-04-13
    Md. Saiful Islam; Bojie Shen; Can Wang; David Taniar; Junhu Wang

    This paper presents a novel query for spatial databases, called reverse nearest neighborhood (RNH) query, to discover the neighborhoods that find a query facility as their nearest facility among other facilities in the dataset. Unlike a reverse nearest neighbor (RNN) query, an RNH query emphasizes on group of users instead of an individual user. More specifically, given a set of user locations U, a

  • A-BI+: A framework for Augmented Business Intelligence
    Inform. Syst. (IF 2.466) Pub Date : 2020-03-14
    Matteo Francia; Matteo Golfarelli; Stefano Rizzi

    Augmented reality allows users to superimpose digital information (typically, of operational type) upon real-world objects. The synergy of analytical frameworks and augmented reality opens the door to a new wave of situated analytics, in which users within a physical environment are provided with immersive analyses of local contextual data. In this paper, we propose an approach named A-BI+ (Augmented

  • A survey on graph-based methods for similarity searches in metric spaces
    Inform. Syst. (IF 2.466) Pub Date : 2020-02-25
    Larissa C. Shimomura; Rafael Seidi Oyamada; Marcos R. Vieira; Daniel S. Kaster

    Technology development has accelerated the volume growth of complex data, such as images, videos, time series, and georeferenced data. Similarity search is a widely used approach to retrieve complex data, which aims at retrieving similar data according to intrinsic characteristics of the data. Therefore, to facilitate the retrieval of complex data using similarity searches, one needs to organize large

  • Using agile methodologies for adopting COBIT
    Inform. Syst. (IF 2.466) Pub Date : 2020-02-19
    Ana Cláudia Amorim; Miguel Mira da Silva; Rúben Pereira; Margarida Gonçalves

    COBIT 5 is a widely-used framework for implementing sound governance of enterprise IT (GEIT). Currently, the ISACA’s official implementation solution follows a sequentially ordered process, raising several issues related with lack of commitment from top management and misaligned solutions. Nevertheless, new project life-cycle strategies have emerged along with the agile paradigm for project management

  • Re-ranking via local embeddings: A use case with permutation-based indexing and the nSimplex projection
    Inform. Syst. (IF 2.466) Pub Date : 2020-02-13
    Lucia Vadicamo; Claudio Gennaro; Fabrizio Falchi; Edgar Chávez; Richard Connor; Giuseppe Amato

    Approximate Nearest Neighbor (ANN) search is a prevalent paradigm for searching intrinsically high dimensional objects in large-scale data sets. Recently, the permutation-based approach for ANN has attracted a lot of interest due to its versatility in being used in the more general class of metric spaces. In this approach, the entire database is ranked by a permutation distance to the query. Typically

  • Bitpart: Exact metric search in high(er) dimensions
    Inform. Syst. (IF 2.466) Pub Date : 2020-02-04
    Alan Dearle; Richard Connor

    We define BitPart (Bitwise representations of binary Partitions), a novel exact search mechanism intended for use in high-dimensional spaces. In outline, a fixed set of reference objects is used to define a large set of regions within the original space, and each data item is characterised according to its containment within these regions. In contrast with other mechanisms only a subset of this information

  • A comprehensive analysis of delayed insertions in metric access methods
    Inform. Syst. (IF 2.466) Pub Date : 2020-01-11
    Humberto Razente; Maria Camila N. Barioni; Regis M. Santos Sousa

    Similarity queries are fundamental operations for applications that deal with complex data. This paper presents MIA (Metric Indexing Assisted by auxiliary memory with limited capacity), a new delayed insertion approach that can be employed to create enhanced dynamic metric access methods through short-term memories. We present a comprehensive evaluation of delayed insertion methods for metric access

  • An Alternative View on Data Processing Pipelines from the DOLAP 2019 Perspective
    Inform. Syst. (IF 2.466) Pub Date : 2019-12-27
    Oscar Romero; Robert Wrembel; Il-Yeol Song

    Data science requires constructing data processing pipelines (DPPs), which span diverse phases such as data integration, cleaning, pre-processing, and analysis. However, current solutions lack a strong data engineering perspective. As consequence, DPPs are error-prone, inefficient w.r.t. human efforts, and inefficient w.r.t. execution time. We claim that DPP design, development, testing, deployment

  • Detecting coherent explorations in SQL workloads
    Inform. Syst. (IF 2.466) Pub Date : 2019-12-09
    Verónika Peralta; Patrick Marcel; Willeme Verdeaux; Aboubakar Sidikhy Diakhaby

    This paper presents a proposal aiming at better understanding a workload of SQL queries and detecting coherent explorations hidden within the workload. In particular, our work investigates SQLShare (Jain et al., 2016), a database-as-a-service platform targeting scientists and data scientists with minimal database experience, whose workload was made available to the research community. According to

  • Two-stage optimization for machine learning workflow
    Inform. Syst. (IF 2.466) Pub Date : 2019-12-09
    Alexandre Quemy

    Machine learning techniques play a preponderant role in dealing with massive amount of data and are employed in almost every possible domain. Building a high quality machine learning model to be deployed in production is a challenging task, from both, the subject matter experts and the machine learning practitioners. For a broader adoption and scalability of machine learning systems, the construction

  • Feedback driven improvement of data preparation pipelines
    Inform. Syst. (IF 2.466) Pub Date : 2019-12-06
    Nikolaos Konstantinou; Norman W. Paton

    Data preparation, whether for populating enterprise data warehouses or as a precursor to more exploratory analyses, is recognised as being laborious, and as a result is a barrier to cost-effective data analysis. Several steps that recur within data preparation pipelines are amenable to automation, but it seems important that automated decisions can be refined in the light of user feedback on data products

  • CoPModL: Construction Process Modeling Language and Satisfiability Checking
    Inform. Syst. (IF 2.466) Pub Date : 2019-11-27
    Elisa Marengo; Werner Nutt; Matthias Perktold

    Process modeling has been widely investigated in the literature and several general purpose approaches have been introduced, addressing a variety of domains. However, generality goes to the detriment of the possibility to model details and peculiarities of a particular application domain. As acknowledged by the literature, known approaches predominantly focus on one aspect between control flow and

  • Formalising and animating multiple instances in BPMN collaborations
    Inform. Syst. (IF 2.466) Pub Date : 2019-11-01
    Flavio Corradini; Chiara Muzi; Barbara Re; Lorenzo Rossi; Francesco Tiezzi

    The increasing adoption of modelling methods contributes to a better understanding of the flow of processes, from the internal behaviour of a single organisation to a wider perspective where several organisations exchange messages. In this regard, BPMN collaborations provide a suitable modelling abstraction. Even if this is a widely accepted notation, only a limited effort has been expended in formalising

  • A DSL for WSN software components coordination
    Inform. Syst. (IF 2.466) Pub Date : 2019-10-31
    Marcos Aurélio Carrero; Martin A. Musicante; Aldri Luiz dos Santos; Carmem S. Hara

    Wireless Sensor Networks (WSNs) have become an integral part of urban scenarios. They are usually composed of a large number of devices. Developing systems for such networks is a hard task and often involves validation on simulation environments before deployment on real settings. Component-based development allows systems to be built from reusable, existing components that share a common interface

  • Aligning observed and modelled behaviour by maximizing synchronous moves and using milestones
    Inform. Syst. (IF 2.466) Pub Date : 2019-10-26
    Vincent Bloemen; Sebastiaan van Zelst; Wil van der Aalst; Boudewijn van Dongen; Jaco van de Pol

    Given a process model and an event log, conformance checking aims to relate the two together, e.g. to detect discrepancies between them. For the synchronous product net of the process and a log trace, we can assign different costs to a synchronous move, and a move in the log or model. By computing a path through this (synchronous) product net, whilst minimizing the total cost, we create a so-called

  • BINet: Multi-perspective business process anomaly classification
    Inform. Syst. (IF 2.466) Pub Date : 2019-10-26
    Timo Nolle; Stefan Luettgen; Alexander Seeliger; Max Mühlhäuser

    In this paper, we introduce BINet, a neural network architecture for real-time multi-perspective anomaly detection in business process event logs. BINet is designed to handle both the control flow and the data perspective of a business process. Additionally, we propose a set of heuristics for setting the threshold of an anomaly detection algorithm automatically. We demonstrate that BINet can be used

  • Detecting trend deviations with generic stream processing patterns
    Inform. Syst. (IF 2.466) Pub Date : 2019-10-22
    Massiva Roudjane; Djamal Rebaïne; Raphaël Khoury; Sylvain Hallé

    Information systems produce different types of event logs; in many situations, it may be desirable to look for trends inside these logs. We show how trends of various kinds can be computed over such logs in real time, using a generic framework called the trend distance workflow. Many common computations on event streams turn out to be special cases of this workflow, depending on how a handful of workflow

  • Service contract modeling in Enterprise Architecture: An ontology-based approach
    Inform. Syst. (IF 2.466) Pub Date : 2019-10-18
    Cristine Griffo; João Paulo A. Almeida; Giancarlo Guizzardi; Julio Cesar Nardi

    Service contracts bind parties legally, regulating their behavior in the scope of a (business) service relationship. Given that there are legal consequences attached to service contracts, understanding the elements of a contract is key to managing services in an enterprise. After all, provisions in a service contract and in legislation establish obligations and rights for service providers and customers

  • Enabling runtime flexibility in data-centric and data-driven process execution engines
    Inform. Syst. (IF 2.466) Pub Date : 2019-10-17
    Kevin Andrews; Sebastian Steinau; Manfred Reichert

    Contemporary process management systems support users during the execution of predefined business processes. However, when unforeseen situations occur, which are not part of the process model serving as the template for process execution, contemporary technology is often unable to offer adequate user support. One solution to this problem is to allow for ad-hoc changes to process models, i.e., changes

  • Characterizing client usage patterns and service demand for car-sharing systems
    Inform. Syst. (IF 2.466) Pub Date : 2019-10-11
    Victor A. Alencar; Felipe Rooke; Michele Cocca; Luca Vassio; Jussara Almeida; Alex Borges Vieira

    The understanding of the mobility on urban spaces is useful for the creation of smarter and sustainable cities. However, getting data about urban mobility is challenging, since only a few companies have access to accurate and updated data, that is also privacy-sensitive. In this work, we characterize three distinct car-sharing systems which operate in Vancouver (Canada) and nearby regions, gathering

  • How meaningful are similarities in deep trajectory representations?
    Inform. Syst. (IF 2.466) Pub Date : 2019-10-11
    Saeed Taghizadeh; Abel Elekes; Martin Schäler; Klemens Böhm

    Finding similar trajectories is an important task in moving object databases. However, classical similarity models face several limitations, including scalability and robustness. Recently, an approach named t2vec proposed transforming trajectories into points in a high dimensional vector space, and this transformation approximately keeps distances between trajectories. t2vec overcomes that scalability

  • Speed prediction in large and dynamic traffic sensor networks
    Inform. Syst. (IF 2.466) Pub Date : 2019-10-11
    Regis Pires Magalhaes; Francesco Lettich; Jose Antonio Macedo; Franco Maria Nardini; Raffaele Perego; Chiara Renso; Roberto Trani

    Smart cities are nowadays equipped with pervasive networks of sensors that monitor traffic in real-time and record huge volumes of traffic data. These datasets constitute a rich source of information that can be used to extract knowledge useful for municipalities and citizens. In this paper we are interested in exploiting such data to estimate future speed in traffic sensor networks, as accurate predictions

  • A deep view-point language and framework for projective modeling
    Inform. Syst. (IF 2.466) Pub Date : 2019-09-18
    Colin Atkinson; Christian Tunjic

    Most view-based modeling approaches are today based on a “synthetic” approach in which the views hold all the information modeled about a system and are kept consistent using explicit, inter-view correspondence rules. The alternative “projective” approach, in which the contents of views are “projected” from a single underlying model on demand, is far less widely used due to the lack of suitable conceptual

  • Formal foundations for responsible application integration
    Inform. Syst. (IF 2.466) Pub Date : 2019-09-18
    Daniel Ritter; Stefanie Rinderle-Ma; Marco Montali; Andrey Rivkin

    Enterprise Application Integration (EAI) constitutes the cornerstone in enterprise IT landscapes that are characterized by heterogeneity and distribution. Starting from established Enterprise Integration Patterns (EIPs) such as Content-based Router and Aggregator, EIP compositions are built to describe, implement, and execute integration scenarios. The EIPs and their compositions must be correct at

  • A fully spatial personalized differentially private mechanism to provide non-uniform privacy guarantees for spatial databases
    Inform. Syst. (IF 2.466) Pub Date : 2020-04-08
    Nadia Niknami; Mahdi Abadi; Fatemeh Deldar

    Spatial databases are essential to applications in a wide variety of domains. One of the main privacy concerns when answering statistical queries, such as range counting queries, over a spatial database is that an adversary observing changes in query answers may be able to determine whether or not a particular geometric object is present in the database. Differential privacy addresses this concern

  • Winter is here! A decade of cache-based side-channel attacks, detection & mitigation for RSA
    Inform. Syst. (IF 2.466) Pub Date : 2020-04-06
    Maria Mushtaq; Muhammad Asim Mukhtar; Vianney Lapotre; Muhammad Khurram Bhatti; Guy Gogniat

    Timing-based side-channels play an important role in exposing the state of a process execution on underlying hardware by revealing information about timing and access patterns. Side-channel attacks (SCAs) are powerful cryptanalysis techniques that focus on the underlying implementation of cryptographic ciphers during execution rather than attacking the structure of cryptographic functions. This paper

  • An efficient algorithm for approximated self-similarity joins in metric spaces
    Inform. Syst. (IF 2.466) Pub Date : 2020-02-24
    Sebastián Ferrada; Benjamin Bustos; Nora Reyes

    Similarity join is a key operation in metric databases. It retrieves all pairs of elements that are similar. Solving such a problem usually requires comparing every pair of objects of the datasets, even when indexing and ad hoc algorithms are used. We propose a simple and efficient algorithm for the computation of the approximated k nearest neighbor self-similarity join. This algorithm computes Θ(n3∕2)

  • A-Cure: An accurate information reconstruction from inaccurate data sources
    Inform. Syst. (IF 2.466) Pub Date : 2020-02-17
    Jiawei Xu; Vladimir Zadorozhny; John Grant

    We address the challenge of reconstructing historical information from aggregated, possibly inaccurate historical reports. For example, given a mixture of accurate and inaccurate monthly and weekly sums, how can we find accurately the daily counts of people infected with flu? We propose an approach, called A-Cure, that performs automatic data reconstruction from a combination of accurate and inaccurate

  • On the declarative paradigm in hybrid business process representations: A conceptual framework and a systematic literature study
    Inform. Syst. (IF 2.466) Pub Date : 2020-01-24
    Amine Abbad Andaloussi; Andrea Burattin; Tijs Slaats; Ekkart Kindler; Barbara Weber

    Process modeling plays a central role in the development of today’s process-aware information systems both on the management level (e.g., providing input for requirements elicitation and fostering communication) and on the enactment level (providing a blue-print for process execution and enabling simulation). The literature comprises a variety of process modeling approaches proposing different modeling

  • Clustering biomedical and gene expression datasets with kernel density and unique neighborhood set based vein detection
    Inform. Syst. (IF 2.466) Pub Date : 2020-01-23
    Md Anisur Rahman; Li-Minn Ang; Kah Phooi Seng

    It is a crucial need for a clustering technique to produce high-quality clusters from biomedical and gene expression datasets without requiring any user inputs. Therefore, in this paper we present a clustering technique called KUVClust that produces high-quality clusters when applied on biomedical and gene expression datasets without requiring any user inputs. The KUVClust algorithm uses three concepts

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