• Title/Summary/Keyword: workflow intelligence

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A Workflow-based Social Network Intelligence Discovery Algorithm (워크플로우 소셜네트워크 인텔리전스 발견 알고리즘)

  • Kim, Kwang-Hoon
    • Journal of Internet Computing and Services
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    • v.13 no.2
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    • pp.73-86
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    • 2012
  • This paper theoretically derives an algorithm to discover a new type of social networks from workflow models, which is termed workflow-based social network intelligence. In general, workflow intelligence (or business process intelligence) technology consists of four types of techniques that discover, analyze, monitor and control, and predict from workflow models and their execution histories. So, this paper proposes an algorithm, which is termed ICN-based workflow-based social network intelligence discovery algorithm, to be classified into the type of discovery techniques, which are able to discover workflow-based social network intelligence that are formed among workflow performers through a series of workflow models and their executions, In order particularly to prove the correctness and feasibility of the proposed algorithm, this paper tries to apply the algorithm to a specific workflow model and to show that it is able to generate its corresponding workflow-based social network intelligence.

Modeling, Discovering, and Visualizing Workflow Performer-Role Affiliation Networking Knowledge

  • Kim, Haksung;Ahn, Hyun;Kim, Kwanghoon Pio
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.2
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    • pp.691-708
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    • 2014
  • This paper formalizes a special type of social networking knowledge, which is called "workflow performer-role affiliation networking knowledge." A workflow model specifies execution sequences of the associated activities and their affiliated relationships with roles, performers, invoked-applications, and relevant data. In Particular, these affiliated relationships exhibit a stream of organizational work-sharing knowledge and utilize business process intelligence to explore resources allotting and planning knowledge concealed in the corresponding workflow model. In this paper, we particularly focus on the performer-role affiliation relationships and their implications as organizational and business process intelligence in workflow-driven organizations. We elaborate a series of theoretical formalisms and practical implementation for modeling, discovering, and visualizing workflow performer-role affiliation networking knowledge, and practical details as workflow performer-role affiliation knowledge representation, discovery, and visualization techniques. These theoretical concepts and practical algorithms are based upon information control net methodology for formally describing workflow models, and the affiliated knowledge eventually represents the various degrees of involvements and participations between a group of performers and a group of roles in a corresponding workflow model. Finally, we summarily describe the implications of the proposed affiliation networking knowledge as business process intelligence, and how worthwhile it is in discovering and visualizing the knowledge in workflow-driven organizations and enterprises that produce massively parallel interactions and large-scaled operational data collections through deploying and enacting massively parallel and large-scale workflow models.

A Workflow-based Affiliation Network Knowledge Discovery Algorithm (워크플로우 협력네트워크 지식 발견 알고리즘)

  • Kim, Kwang-Hoon
    • Journal of Internet Computing and Services
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    • v.13 no.2
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    • pp.109-118
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    • 2012
  • This paper theoretically derives an algorithm to discover a new type of workflow-based knowledge from workflow models, which is termed workflow-based affiliation network knowledge. In general, workflow intelligence (or business process intelligence) technology consists of four types of techniques that discover, analyze, monitor and control, and predict a series of workflow-based knowledge from workflow models and their execution histories. So, this paper proposes a knowledge discovery algorithm which is able to discover workflow-based affiliation networks that represent the association and participation relationships between activities and performers defined in ICN-based workflow models. In order particularly to prove the correctness and feasibility of the proposed algorithm, this paper tries to apply the algorithm to a specific workflow model and to show that it is able to derive its corresponding workflow-based affiliation network knowledge.

A GraphML-based Visualization Framework for Workflow-Performers' Closeness Centrality Measurements

  • Kim, Min-Joon;Ahn, Hyun;Park, Minjae
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.8
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    • pp.3216-3230
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    • 2015
  • A hot-issued research topic in the workflow intelligence arena is the emerging topic of "workflow-supported organizational social networks." These specialized social networks have been proposed to primarily represent the process-driven work-sharing and work-collaborating relationships among the workflow-performers fulfilling a series of workflow-related operations in a workflow-supported organization. We can discover those organizational social networks, and visualize its analysis results as organizational knowledge. In this paper, we are particularly interested in how to visualize the degrees of closeness centralities among workflow-performers by proposing a graphical representation schema based on the Graph Markup Language, which is named to ccWSSN-GraphML. Additionally, we expatiate on the functional expansion of the closeness centralization formulas so as for the visualization framework to handle a group of workflow procedures (or a workflow package) with organizational workflow-performers.

A Study of Artificial Intelligence Generated 3D Engine Animation Workflow

  • Chenghao Wang;Jeanhun Chung
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.286-292
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    • 2023
  • This article is set against the backdrop of the rapid development of the metaverse and artificial intelligence technologies, and aims to explore the possibility and potential impact of integrating AI technology into the traditional 3D animation production process. Through an in-depth analysis of the differences when merging traditional production processes with AI technology, it aims to summarize a new innovative workflow for 3D animation production. This new process takes full advantage of the efficiency and intelligent features of AI technology, significantly improving the efficiency of animation production and enhancing the overall quality of the animations. Furthermore, the paper delves into the creative methods and developmental implications of artificial intelligence technology in real-time rendering engines for 3D animation. It highlights the importance of these technologies in driving innovation and optimizing workflows in the field of animation production, showcasing how they provide new perspectives and possibilities for the future development of the animation industry.

Workflow Process-Aware Data Cubes and Analysis (워크플로우 프로세스 기반 데이터 큐브 및 분석)

  • Jin, Min-hyuck;Kim, Kwang-hoon Pio
    • Journal of Internet Computing and Services
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    • v.19 no.6
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    • pp.83-89
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    • 2018
  • In workflow process intelligence and systems, workflow process mining and analysis issues are becoming increasingly important. In order to improve the quality of workflow process intelligence, it is essential for an efficient and effective data center storing workflow enactment event logs to be provisioned in carrying out the workflow process mining and analytics. In this paper, we propose a three-dimensional process-aware datacube for organizing workflow enterprise data centers to efficiently as well as effectively store the workflow process enactment event logs in the XES format. As a validation step, we carry out an experimental process mining to show how much perfectly the process-aware datacubes are suitable for discovering workflow process patterns and its analytical knowledge, like enacted proportions and enacted work transferences, from the workflow process enactment event histories. Finally, we confirmed that it is feasible to discover the fundamental control-flow patterns of workflow processes through the implemented workflow process mining system based on the process-aware data cube.

A Control Path Analysis Mechanism for Workflow Mining (워크플로우 마이닝을 위한 제어 경로 분석 메커니즘)

  • Min Jun-Ki;Kim Kwang-Hoon;Chung Jung-Su
    • Journal of Internet Computing and Services
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    • v.7 no.1
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    • pp.91-99
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    • 2006
  • This paper proposes a control path analysis mechanism to be used in the workflow mining framework maximizing the workflow traceability and re discoverability by analyzing the total sequences of the control path perspective of a workflow model and by rediscovering their runtime enactment history from the workflow log information. The mechanism has two components One is to generate the total sequences of the control paths from a workflow mode by transforming it to a control path decision tree, and the other is to rediscover the runtime enactment history of each control path out of the total sequences from the corresponding workflow's execution logs. Eventually, these rediscovered knowledge and execution history of a workflow model make up a control path oriented intelligence of the workflow model. which ought to be an essential ingredient for maintaining and reengineering the qualify of the workflow model. Based upon the workflow intelligence, it is possible for the workflow model to be gradually refined and finally maximize its qualify by repeatedly redesigning and reengineering during its whole life long time period.

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A Stochastic Work-Handover Relationship Model in Workflow-supported Social Networks (워크플로우 기반 소셜 네트워크의 확률적 업무전달 관계 모델)

  • Ahn, Hyun;Kim, Kwanghoon
    • Journal of Internet Computing and Services
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    • v.16 no.5
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    • pp.59-66
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    • 2015
  • A stochastic modeling approach as a mathematical method for workflow intelligence is widely used for analyzing and simulating workflow models in the literature. In particular, as a resource-centric modeling approach, this paper proposes a stochastic model to represent work-handover relationships between performers in a workflow-supported social network. Calculating probabilities for the work-handover relationships are determined by two types of probabilities. One is the work-transition probability between activities, and the other is the task assignment probability between activities and performers. In this paper, we describe formal definitions of stochastic workflow models and stochastic work-handover relationship models, as well. Then, we propose an algorithm for extracting a stochastic work-handover relationship model from a stochastic workflow model. As a consequence, the proposed model ought to be useful in performing resource-centric workflow simulations and model-log comparison analyses.

A Theoretical Framework for Closeness Centralization Measurements in a Workflow-Supported Organization

  • Kim, Min-Joon;Ahn, Hyun;Park, Min-Jae
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.9
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    • pp.3611-3634
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    • 2015
  • In this paper, we build a theoretical framework for quantitatively measuring and graphically representing the degrees of closeness centralization among performers assigned to enact a workflow procedure. The degree of closeness centralization of a workflow-performer reflects how near the performer is to the other performers in enacting a corresponding workflow model designed for workflow-supported organizational operations. The proposed framework comprises three procedural phases and four functional transformations, such as discovery, analysis, and quantitation phases, which carry out ICN-to-WsoN, WsoN-to-SocioMatrix, SocioMatrix-to-DistanceMatrix, and DistanceMatrix-to-CCV transformations. We develop a series of algorithmic formalisms for the procedural phases and their transformative functionalities, and verify the proposed framework through an operational example. Finally, we expatiate on the functional expansion of the closeness centralization formulas so as for the theoretical framework to handle a group of workflow procedures (or a workflow package) with organization-wide workflow-performers.

Disjunctive Process Patterns Refinement and Probability Extraction from Workflow Logs

  • Kim, Kyoungsook;Ham, Seonghun;Ahn, Hyun;Kim, Kwanghoon Pio
    • Journal of Internet Computing and Services
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    • v.20 no.3
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    • pp.85-92
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    • 2019
  • In this paper, we extract the quantitative relation data of activities from the workflow event log file recorded in the XES standard format and connect them to rediscover the workflow process model. Extract the workflow process patterns and proportions with the rediscovered model. There are four types of control-flow elements that should be used to extract workflow process patterns and portions with log files: linear (sequential) routing, disjunctive (selective) routing, conjunctive (parallel) routing, and iterative routing patterns. In this paper, we focus on four of the factors, disjunctive routing, and conjunctive path. A framework implemented by the authors' research group extracts and arranges the activity data from the log and converts the iteration of duplicate relationships into a quantitative value. Also, for accurate analysis, a parallel process is recorded in the log file based on execution time, and algorithms for finding and eliminating information distortion are designed and implemented. With these refined data, we rediscover the workflow process model following the relationship between the activities. This series of experiments are conducted using the Large Bank Transaction Process Model provided by 4TU and visualizes the experiment process and results.