Process Remaining Time Prediction Using Query Catalogs

Bolt, Alfredo; Sepúlveda, Marcos

doi:10.1007/978-3-319-06257-0_5

Cited by 14 publications

(12 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Having analyzed the discriminative studies, we have observed that they tend to mix different encoding types [12] or different bucketing types [18], while some combinations thereof have not been explored. As such, in our benchmark, we decided to evaluate all feasible combinations of canonical encoding and bucketing types, 5 including those that have not been used in any existing approach in the literature. In this way, we will be able to assess the benefits of each combination, while abstracting implementation nuances of each individual primary method.…”

Section: Discussionmentioning

confidence: 99%

“…Bolt and Sepúlveda [5] exploit query catalogs to store the information about the process behavior. Such catalogs are groups of partial traces (annotated with additional information about each partial trace) that have occurred in an event log, and are then used to estimate the remaining time of new executions of the process.…”

Section: Process Awarenessmentioning

confidence: 99%

“…The indicators are then combined by means of a prediction function, which allows for highlighting the possibility of transgressing deadlines. Conversely, Bolt and Sepúlveda [5] calculate remaining time based on the average time in the catalog which the partial trace belongs to, without taking into account distributions and confidence intervals.…”

Section: Family Of Algorithmsmentioning

confidence: 99%

See 2 more Smart Citations

Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring

Verenich

Dumas

Rosa

et al. 2019

ACM Trans. Intell. Syst. Technol.

139

View full text Add to dashboard Cite

Predictive business process monitoring methods exploit historical process execution logs to generate predictions about running instances (called cases) of a business process, such as the prediction of the outcome, next activity or remaining cycle time of a given process case. These insights could be used to support operational managers in taking remedial actions as business processes unfold, e.g. shifting resources from one case onto another to ensure this latter is completed on time. A number of methods to tackle the remaining cycle time prediction problem have been proposed in the literature. However, due to differences in their experimental setup, choice of datasets, evaluation measures and baselines, the relative merits of each method remain unclear. This article presents a systematic literature review and taxonomy of methods for remaining time prediction in the context of business processes, as well as a cross-benchmark comparison of 16 such methods based on 16 real-life datasets originating from different industry domains.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Process Awarenessmentioning

confidence: 99%

Section: Family Of Algorithmsmentioning

confidence: 99%

See 1 more Smart Citation

Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring

Verenich

Dumas

Rosa

et al. 2019

ACM Trans. Intell. Syst. Technol.

139

View full text Add to dashboard Cite

show abstract

“…Generally, one assumes that each event has a timestamp and belongs to one case (process instance). Process mining enables discovery of a process model from a log, measuring the conformance of a log to a model, enhancement of a process model based on logs, and predictions of process properties [17,18].…”

Section: Bpm-oriented Systemsmentioning

confidence: 99%

From event streams to process models and back: Challenges and opportunities

Soffer

Hinze

Koschmider

et al. 2019

Information Systems

View full text Add to dashboard Cite

The domains of complex event processing (CEP) and business process management (BPM) have different origins but for many aspects draw on similar concepts. While specific combinations of BPM and CEP have attracted research attention, resulting in solutions to specific problems, we attempt to take a broad view at the opportunities and challenges involved. We first illustrate these by a detailed example from the logistics domain. We then propose a mapping of this area into four quadrants -two quadrants drawing from CEP to create or extend process models and two quadrants starting $ This paper is an outcome of discussions and collaborations that were initiated at the Dagstuhl seminar 16341 on "Integrating Process-Oriented and Event-Based Systems" from a process model to address how it can guide CEP. Existing literature is reviewed and specific challenges and opportunities are indicated for each of these quadrants. Based on this mapping, we identify challenges and opportunities that recur across quadrants and can be considered as the core issues of this combination. We suggest that addressing these issues in a generic manner would form a sound basis for future applications and advance this area significantly.

show abstract

“…There are different ways to execute a constraint-based process model while fulfilling the constraints, i.e., there are several related enactment plans. 5 The different valid execution alternatives, however, can greatly vary in respect to their quality, i.e., how well different performance objective functions can be achieved. Such objective functions of the BPs are the functions to be optimized during the BP enactment, e.g., minimization of the overall completion time.…”

Section: Constraint-based Bp Modelsmentioning

confidence: 99%

Time prediction on multi-perspective declarative business processes

et al. 2018

View full text Add to dashboard Cite

 Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  You may not further distribute the material or use it for any profit-making activity or commercial gain  You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

show abstract

Process Remaining Time Prediction Using Query Catalogs

Cited by 14 publications

References 6 publications

Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring

Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring

From event streams to process models and back: Challenges and opportunities

Time prediction on multi-perspective declarative business processes

Contact Info

Product

Resources

About