Interactive workflow mining—requirements, concepts and implementation

Hammori, Markus; Herbst, Joachim; Kleiner, Niko

doi:10.1016/j.datak.2005.02.006

Cited by 25 publications

(5 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, an end-user is likely to prefer process discovery algorithms that are less stringent on computational requirements. In practice, shorter run times will encourage the end-user to interactively explore the event log, applying various filters, and parameter settings [16,37]. Reporting run times is perhaps unfair.…”

Section: Run Timementioning

confidence: 97%

Process discovery in event logs: An application in the telecom industry

Goedertier

Weerdt

Martens

et al. 2011

Applied Soft Computing

View full text Add to dashboard Cite

Section: Run Timementioning

confidence: 97%

Process discovery in event logs: An application in the telecom industry

Goedertier

Weerdt

Martens

et al. 2011

Applied Soft Computing

View full text Add to dashboard Cite

“…Many process mining algorithms have been proposed in the last years [38][39][40]32,23,48,22,15,44]. Of relevance to this paper is the distinction between precise and noisy mining algorithms.…”

Section: Process Miningmentioning

confidence: 98%

“…Noisy mining algorithms [3,11,28,23,22,[46][47][48] in their majority use the frequency of the temporal order relation between two activities to infer their dependency, and thus infrequent dependencies in the log may not be modeled in the resultant process model. An exception to the frequency based approach is the work on genetic mining [15,14] which uses a search based on genetic algorithms with an explicit representation of the ordering among models.…”

Section: Process Miningmentioning

confidence: 99%

Algorithms for anomaly detection of traces in logs of process aware information systems

Bezerra

Wainer

2013

Information Systems

102

View full text Add to dashboard Cite

a b s t r a c tThis paper discusses four algorithms for detecting anomalies in logs of process aware systems. One of the algorithms only marks as potential anomalies traces that are infrequent in the log. The other three algorithms: threshold, iterative and sampling are based on mining a process model from the log, or a subset of it. The algorithms were evaluated on a set of 1500 artificial logs, with different profiles on the number of anomalous traces and the number of times each anomalous traces was present in the log. The sampling algorithm proved to be the most effective solution. We also applied the algorithm to a real log, and compared the resulting detected anomalous traces with the ones detected by a different procedure that relies on manual choices.

show abstract

“…The idea of interactive mining of models is previously explored in process mining applications [29]. However, our protocol refinement approach is original, and to the best of our knowledge, no support is provided for refinement of discovered models to compensate for log imperfection.…”

Section: Model Refinementmentioning

confidence: 98%

Deriving Protocol Models from Imperfect Service Conversation Logs

Motahari-Nezhad

Saint-Paul

Benatallah

et al. 2008

IEEE Trans. Knowl. Data Eng.

View full text Add to dashboard Cite

Understanding the business (interaction) protocol supported by a service is very important for both clients and service providers: It allows developers to know how to write clients that interact with a service, and it allows development tools and runtime middleware to deliver functionalities that simplifies the service development life cycle. It also greatly facilitates the monitoring, visualization, and aggregation of interaction data. This paper presents an approach for discovering protocol models from real-world service interaction logs. It presents a novel discovery algorithm, which is widely applicable, robust to different kinds of imperfections often present in real-world service logs, and able to derive protocols of small sizes targeted for human understanding. As inferring the most precise and concise model is not always possible from imperfect service logs using purely automated method, the paper presents a novel method for user-driven refinement of the discovered protocol models. The proposed approach has been implemented and experimental results show its viability on both synthetic and real-world data sets.Index Terms-Web services, business protocols, noise handling in service logs, protocol discovery, protocol refinement.

show abstract

Interactive workflow mining—requirements, concepts and implementation

Cited by 25 publications

References 20 publications

Process discovery in event logs: An application in the telecom industry

Process discovery in event logs: An application in the telecom industry

Algorithms for anomaly detection of traces in logs of process aware information systems

Deriving Protocol Models from Imperfect Service Conversation Logs

Contact Info

Product

Resources

About