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检索条件"丛书名=Lecture Notes in Business Information Processing"

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Resource Allocation in Recommender Systems for Global KPI Improvement 21st

Resource Allocation in Recommender Systems for Global KPI Im...

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21st International Conference on business Process Management (BPM)

作者： Padella, Alessandro de Leoni, Massimiliano Univ Padua Padua Italy

ISBN: (纸本)9783031416224;9783031416231

Process-aware Recommender systems are information systems designed to monitor the execution of processes, predict their outcomes, and suggest effective interventions to achieve better results, with respect to reference KPIs (Key Performance Indicators). Interventions typically consist of suggesting an activity to be assigned to a certain resource. State of the art typically proposes interventions for single cases in isolation. However, since resources are shared among cases, this might impact the effectiveness of the available interventions for other cases that would require one. As result, the overall KPI improvement is partially hampered. This paper proposes an approach to assign resources to needed cases, aiming to improve the overall KPI values for all cases together, namely the summation of KPI values for all cases. Experiments conducted on two real-life case studies illustrate that globally considering all needing cases together allows a better global KPI improvement, compared with a more greedy approach where interventions are proposed one after the other.

关键词： Process Improvement Process Prescriptive Analytics Recommender Systems Resource Allocation Resource Experience

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Current Challenges and Opportunities in Enterprise Architecture: Insights from 950+LeanIX Customers 12th

Current Challenges and Opportunities in Enterprise Architect...

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12th Enterprise Engineering Working Conference on Advances in Enterprise Engineering (EEWC)

作者： Aldea, Adina LeanIX Prins Bernhardpl 200 NL-1097 JB Amsterdam Netherlands

ISBN: (纸本)9783031341748;9783031341755

Data-driven architecture is a new paradigm promoted by LeanIX that focuses on making Enterprise Architecture accessible to a wider audience of stakeholders in organizations, to increase data quality and provide transparency when undergoing organizational transformations. This democratization of Enterprise Architecture allows organizations to transform faster and take advantage of trends such as the API Economy, Software-as-a-Service, and Citizen Developers with low-code applications. From this perspective, in this paper, we present the most common challenges that organizations face in their Enterprise Architecture practice due to siloed information and lack of communication between stakeholders. Furthermore, using tools like Excel and PowerPoint to manage the architecture poses challenges due to obsolete data, inability to create meaningful analyses and having multiple sources of truth. In the case of C&A, Helvetia and Marc O'Polo we present how having a modern data-driven Enterprise Architecture has helped these organizations with addressing their challenges and transforming quickly. Finally, we present our ideas on avenues for advancing the field of Enterprise Architecture from a research and practice perspective.

关键词： Data-driven Enterprise Architecture Enterprise Architecture challenges Enterprise Architecture opportunities

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Flexible Detection of Similar DOM Elements 1

引用

17th International Conference on Web information Systems and Technologies (WEBIST)

作者： Grigera, Julian Cruz Gardey, Juan Rossi, Gustavo Garrido, Alejandra Univ Nacl La Plata LIFIA Fac Informat RA-1900 La Plata Argentina Consejo Nacl Invest Cient & Tecn Buenos Aires DF Argentina CICPBA La Plata Argentina

ISBN: (数字)9783031241970

ISBN: (纸本)9783031241963;9783031241970

Different research fields related to the web require detecting similarity between DOM elements. In the field of information extraction, many approaches emerged to extract structured data from web documents, most of which require comparing sample documents to extract their underlying structure. Other fields of applicability like web augmentation or transcoding also require analyzing structural similarity, but on UI components with smaller structures than full documents, making them unsuitable for the algorithms generally used in information extraction. Instead, these approaches tend to rely on the DOM elements' location, but this does not resist structural changes in the document, and cannot locate similar elements placed in different positions. In this paper we present two flexible algorithms to measure similarity between DOM elements by using a mixed approach that considers both elements' location and inner structure, together with a wrapper induction technique. We evaluated our algorithms with respect to other known approaches in the literature by comparing how they cluster a dataset of 1200+ DOM elements, using a manual clustering as ground truth. Results show that both proposed algorithms outperform all baseline ones. The proposed algorithms run in linear time, so they are faster than most approaches that analyze structural similarity.

关键词： DOM information extraction Web adaptation

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Analytics Pipeline for Process Mining on Video Data 21st

Analytics Pipeline for Process Mining on Video Data

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21st International Conference on business Process Management (BPM)

作者： Lepsien, Arvid Koschmider, Agnes Kratsch, Wolfgang Univ Kiel Dept Comp Sci Kiel Germany Univ Bayreuth Chair Business Informat & Proc Analyt Bayreuth Germany Fraunhofer FIT Bayreuth Germany Tech Univ Appl Sci Augsburg Augsburg Germany Fraunhofer FIT Augsburg Germany

ISBN: (纸本)9783031416224;9783031416231

Process mining has shown that it provides valuable insights in terms of uncovering bottlenecks and inefficiencies in processes or identifying tasks for automation. However, process mining techniques expect structured input data that is at a high (business) level of abstraction. Recently, the benefits of process mining for unstructured data which is at a much lower level of abstraction have been demonstrated, e.g., for IoT data or time series data. It can be expected that the demand for methods efficiently processing these kinds of data for process mining will continuously increase. Hence, in this paper, we present an approach that allows the translation of video data into higher-level, discrete event data, thus enabling existing process mining techniques to work on data tracked in videos. Particularly, we used a combination of object tracking, spatio-temporal action detection, and techniques for raising the abstraction level of events. The evaluation results show that meaningful event logs can be extracted from an unlabeled video dataset, validating both the implementation and the feasibility of our approach.

关键词： Process mining Event log extraction Unstructured data Activity recognition

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Serious Game-Based Haptic Modeling - An Application-Oriented Approach for Sequentially Developing New business Models from Tacit Knowledge 13th

Serious Game-Based Haptic Modeling - An Application-Oriented...

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13th International Symposium on business Modeling and Software Design (BMSD)

作者： Gronau, Norbert Teichmann, Malte Webers, Edzard Univ Potsdam August Bebel St 89 D-14482 Potsdam Germany Weizenbaum Inst Networked Soc Hardenbergstr 32 D-10623 Berlin Germany

ISBN: (纸本)9783031367564;9783031367571

The authors propose that while tacit knowledge is a valuable resource for developing new business models, its externalization presents several challenges. One major challenge is that individuals often don't recognize their tacit knowledge resources, while another is the reluctance to share one's knowledge with others. Addressing these challenges, the authors present an application-oriented serious game-based haptic modeling approach for externalize tacit knowledge, which can be used to develop the first versions of business models based on tacit knowledge. Both conceptual and practical design fundamentals are presented based on elaborated theoretical approaches, which were developed with the help of a design science approach. The development of the research process is presented step by step, whereby we focused on the high accessibility of the presented research. Practitioners are presented with guidelines for implementing their serious game projects. Scientists benefit from starting points for their research topics of externalization, internalization, and socialization of tacit knowledge, development of business models, and serious games or gamification. The paper concludes with open research desiderata and questions from the presented research process.

关键词： Serious game Tacit knowledge business model SECI-model Conversion sequences Design science

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A Semiotic Analysis of the Representativeness of BPMN Graphic Elements 13th

A Semiotic Analysis of the Representativeness of BPMN Graphi...

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13th International Symposium on business Modeling and Software Design (BMSD)

作者： Duarte, Evelyne Batista Duarte, Rafael Batista da Silveira, Denis Silva Univ Fed Pernambuco Recife PE Brazil Univ Pernambuco Recife PE Brazil

ISBN: (纸本)9783031367564;9783031367571

business Process Modeling (BPM) has been under considerable attention from business and information technology (IT) communities. It is an important asset in the quest to decrease the gap in communication between these two groups. To contribute to decreasing this gap, this paper presents the execution of a quasi-experiment to verify whether business Process Modelling Notation's (BPMN) graphical elements are representative according to their semantics. Data collected with 89 participants, so far, through a semiotic analysis has shown that the notations' elements are based on symbolic signs, understood due to shared law, while participants showed preference for iconic signs, that have visual relation to the real object.

关键词： business Process Models BPMN Semiotics Analysis Quasi-Experiment

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A Flexible, Extendable and Adaptable Model to Support AI Coaching 22nd

A Flexible, Extendable and Adaptable Model to Support AI Coa...

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22nd International Conference on Perspectives in business Informatics Research (BIR)

作者： Duhan, Ritu Pande, Charuta Martin, Andreas FHNW Univ Appl Sci & Arts Northwestern Switzerlan Intelligent Informat Syst Res Grp Riggenbachstr 16 CH-4600 Olten Switzerland

ISBN: (纸本)9783031431258;9783031431265

We present a model based on coaching definitions, concepts, and theories to support AI coaching. The model represents the evidence-based coaching practice in different coaching domains by identifying the common elements in the coaching process. We then map the elements of the coaching model with Conversational AI design and development strategies to highlight how an AI coach can be instantiated from the model. We showcase the instantiation through an example use case of an HIV coaching chatbot.

关键词： Coaching Conversational AI Design AI Coaching Coaching Model Chatbot

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Machine Learning Based Finding of Similar Sentences from French Clinical notes 1

引用

17th International Conference on Web information Systems and Technologies (WEBIST)

作者： Drame, Khadim Diallo, Gayo Sambe, Gorgoumack Univ Assane Seck Ziguinchor Ziguinchor Senegal Lab Informat & Ingn Innovat Ziguinchor Senegal Univ Bordeaux SISTM INRIA BPH INSERM 1219 F-33000 Bordeaux France

ISBN: (数字)9783031241970

ISBN: (纸本)9783031241963;9783031241970

Finding similar sentences or paragraphs is a key issue when dealing with text redundancy. This is particularly the case in the clinical domain where redundancy in clinical notes makes their secondary use limited. Due to lack of resources, this task is a key challenge for French clinical documents. In this paper, we introduce a semantic similarity computing approach between French clinical sentences based on supervised machine learning algorithms. The proposed approach is implemented in a system called CONCORDIA, for COmputing semaNtic sentenCes for fRench Clinical Documents sImilArity. After briefly reviewing various semantic textual similarity measures reported in the literature, we describe the approach, which relies on Random Forest (RF), Multilayer Perceptron (MLP) and Linear Regression (LR) algorithms to build different supervised models. These models are thereafter used to determine the degrees of semantic similarity between clinical sentences. CONCORDIA is evaluated using traditional evaluation metrics, EDRM (Accuracy in relative distance to the average solution) and Spearman correlation, on standard benchmarks provided in the context of the DEFT 2020 challenge. According to the official results of this challenge, our MLP based model ranked first out of the 15 submitted systems with an EDRM of 0.8217 and a Spearman correlation coefficient of 0.7691. The post-challenge development of CONCORDIA and the experiments performed after the DEFT 2020 edition showed a significant improvement of the performance of the different implemented models. In particular, the new MLP based model achieves a Spearman correlation coefficient of 0.80. On the other hand, the LR one, which combines the output of the MLP model with word embedding similarity scores, obtains the higher Spearman correlation coefficient with a score of 0.8030. Therefore, the experiments show the effectiveness and the relevance of the proposed approach for finding similar sentences on French clinical notes.

关键词： Sentence similarity Machine learning Random forest Multilayer perceptron French clinical notes

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Understanding First-Aid Learning Intention Through Using Social Media: Perceptions from External Emergency Events and Individual Internal Changes 1

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22nd Wuhan International Conference on E-business (WHICEB)

作者： Guo, Huijing Wang, Xifu Liu, Xiaoxiao Ju, Xiaofeng Harbin Inst Technol Sch Management Harbin 150001 Peoples R China Guangzhou First Peoples Hosp Healthcare Simulat Ctr Guangzhou 510180 Peoples R China Xi An Jiao Tong Univ Sch Management Xian 710049 Peoples R China Xi An Jiao Tong Univ China Inst Hosp Dev & Reform Xian 710049 Peoples R China

ISBN: (数字)9783031322990

ISBN: (纸本)9783031322983;9783031322990

Emergency events, such as out-of-hospital cardiac arrest, are China's leading causes of mortality. However, witnesses of emergencies are seldom trained with first-aid measures before emergency events happens. Relative to traditional offline first-aid training methods, social media greatly enhanced audiences' interest in first-aid learning in a more entertaining, time-saving, and labor-saving way. Based on Construal Level Theory (CLT), this study aims to understand the impact of external emergencies (past emergencies experience) on individual internal change (psychological distances) and subsequently generate first-aid learning intention through using social media. As emergencies are severe but not widespread, this study only examines social and spatial dimensions of psychological distance (PD) to broaden the application scenarios of CLT. At the same time, we apply prosociality to measure the individual difference. This study conducts a survey in a first-aid popularization account on Sina Weibo. 348 participants, who had never learned first-aid knowledge and skills before, engaged. Results prove that both PDs and prosociality may be impacted by external emergency experiences, then promote related learning intention. This study also finds that prosociality moderates the relationship between spatial distance and related learning intention. This study roots in an emergency context and broadens the application of CLT in first-aid learning. At the same time, since first-aid training is usually hard to grasp and residents usually do not need complex skills to rescue people in emergency events, we applied social media as our learning context in this study to lower the threshold of first-aid education.

关键词： First-aid learning intention Emergency events Past experience Psychological distances Construal Level Theory Prosociality Social media

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An Approach for Knowledge Graphs-Based User Stories in Agile Methodologies 22nd

An Approach for Knowledge Graphs-Based User Stories in Agile...

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22nd International Conference on Perspectives in business Informatics Research (BIR)

作者： Mancuso, Marco Laurenzi, Emanuele FHNW Univ Appl Sci & Arts Northwestern Switzerlan Riggenbachstr 16 CH-4600 Olten Switzerland

ISBN: (纸本)9783031431258;9783031431265

In this paper, we present AOAME4UserStories, a modelling and ontology-based approach that enables the creation of visual user stories grounded in a knowledge graph. The approach includes an ontology-based domain-specific modelling language - User Story Modelling & Notation (USMN) - and resolves the problem of creating inconsistent user stories in agile software development methodologies such as Scrum. The Design Science Research methodology was followed for the creation of USMN and its implementation in the modelling tool AOAME. The evaluation was conducted by first creating a visual user story reflecting a real-world use case and then by proving the consistent production of knowledge graphs for the given visual story.

关键词： Agile software development Scrum visual user stories knowledge graphs USMN domain-specific modelling language (DSML) ontology-based meta-modelling AOAME4UserStories

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