Operation record based workflow extracting method for personal information management system

Abeta, A.; Kakizaki, Ken'ichi

doi:10.1109/apchi.1998.704224

Cited by 4 publications

(2 citation statements)

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“…• Workflow Knowledge Mining: Related work also includes process and activity mining from various enterprise data stores and user contexts (Abeta & Kakizaki, 1998). Activity centric workflow models have been generated through the mining and correlating of data from transactional systems.…”

Section: Related Workmentioning

confidence: 99%

Stakeholder Ontology and Mining for Improving Complex Services

Ramanathan

Ramnath

2013

International Journal of Information Systems in the Service Sector

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Complex service-oriented organizations (such as IT customer service or the hospital emergency) deal with many challenges due to incoming request types that we characterize as non-routine. Each such request reflects significant variations in the environment and consequently requirements, which drives discovery of processing needs. At the same time such organizations are often challenged with sharing high-cost resources and satisfying multiple stakeholders with different expectations. Performance improvement in this context is particularly challenging and requires new methods. To address this, the authors present an ontology designed for highly dynamic service organizations where traceable workflow data is difficult to obtain and there are many stakeholders. The ontology provides the contextual framework by with useful knowledge can be successfully extracted from mined performance data obtained from scattered sources. Specifically the service ontology 1) obtains tacit knowledge as explicit in-the-micro feedback from workers performing Roles, 2) provides the structure for organizing in-the-small execution data from evolving process and instances, and 3) aggregates process instances metrics into a performance and decision-making facility to align to in-the-large goals of stakeholders. Using actual customer service requests they illustrate the benefits of the ontology for relating aggregated goals to feedback from individual roles of workers. The authors also illustrate the benefits in terms of identifying actionable improvement targets.

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Section: Related Workmentioning

confidence: 99%

Stakeholder Ontology and Mining for Improving Complex Services

Ramanathan

Ramnath

2013

International Journal of Information Systems in the Service Sector

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“…From this viewpoint, we have been researching and developing a system [6,7] that shares and reuses knowledge of work by accumulating schedules systematically based on relations between events. Furthermore, we suggest refining schedules during repeated reuse.…”

Section: Introductionmentioning

confidence: 99%

Operation record based work events grouping method for personal information management system

Abeta

Kakizaki²

Proceedings. The Twenty-Second Annual International Computer Software and Applications Conference (Compsac '98) (Cat. No.98CB 3

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In order to improve the efficiency of any business, it is now very important to reuse knowledge by accumulating it in a computer. We propose a method that accumulates and reuses knowledge of work by automatically extracting it from a user's operation records during ordinary use on a Personal Information Management system (PIM). We assume that related work events on the PIM are input and referred to consecutively by the user. Our method that extracts available knowledge constructs a workflow by grouping all related events and detecting milestones based on the time and order of operating target events. Usually, reference to events is the user's viewing of events on the calendar without involving operations, so recording a target event and time of reference is difficult. In order to record the user's reference behavior exactly, we introduce a balloon-help-based function for event reference support.

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